### Transfer Learning of fMRI Dynamics. (arXiv:1911.06813v1 [eess.IV])

As a mental disorder progresses, it may affect brain structure, but brain function expressed in brain dynamics is affected much earlier. Capturing the moment when brain dynamics express the disorder is crucial for early diagnosis. The traditional approach to this problem via training classifiers either proceeds from handcrafted features or requires large datasets to combat…

### X-ray Multimodal Intrinsic-Speckle-Tracking. (arXiv:1911.06814v1 [eess.IV])

We develop X-ray Multimodal Intrinsic-Speckle-Tracking (MIST), a form of X-ray speckle-tracking that is able to recover both the refractive index decrement and the small-angle X-ray scattering (SAXS) signal of a phase object. MIST is based on combining a Fokker-Planck description of paraxial X-ray optics, with an optical-flow formalism for X-ray speckle-tracking. Only two images need…

### Precise Spatial Memory in Local Random Networks. (arXiv:1911.06921v1 [q-bio.NC])

Self-sustained, elevated neuronal activity persisting on time scales of ten seconds or longer is thought to be vital for aspects of working memory, including brain representations of real space. Continuous-attractor neural networks, one of the most well-known modeling frameworks for persistent activity, have been able to model crucial aspects of such spatial memory. These models…

### Indoor microbiome, environmental characteristics and asthma among junior high school students in Johor Bahru, Malaysia. (arXiv:1911.06946v1 [q-bio.GN])

Indoor microbial diversity and composition are suggested to affect the prevalence and severity of asthma. In this study, we collected floor dust and environmental characteristics from 21 classrooms, and health data related to asthma symptoms from 309 students, in junior high schools in Johor Bahru, Malaysia. Bacterial and fungal composition was characterized by sequencing 16s…

### Highly Sensitive and Label-free Digital Detection of Whole Cell E. coli with Interferometric Reflectance Imaging. (arXiv:1911.06950v1 [q-bio.BM])

Bacterial infectious diseases are a major threat to human health. Timely and sensitive pathogenic bacteria detection is crucial in identifying the bacterial contaminations and preventing the spread of infectious diseases. Due to limitations of conventional bacteria detection techniques there have been concerted research efforts towards development of new biosensors. Biosensors offering label free, whole bacteria…

### Three cooperative mechanisms required for recovery after brain damage. (arXiv:1911.07012v1 [q-bio.NC])

Stroke is one of the main causes of human disabilities. Experimental observations indicate that several mechanisms are activated during the recovery of functional activity after a stroke. Here we unveil how the brain recovers by explaining the role played by three mechanisms: Plastic adaptation, hyperexcitability and synaptogenesis. We consider two different damages in a neural…

### X-ray Multimodal Intrinsic-Speckle-Tracking. (arXiv:1911.06814v1 [eess.IV])

We develop X-ray Multimodal Intrinsic-Speckle-Tracking (MIST), a form of X-ray speckle-tracking that is able to recover both the refractive index decrement and the small-angle X-ray scattering (SAXS) signal of a phase object. MIST is based on combining a Fokker-Planck description of paraxial X-ray optics, with an optical-flow formalism for X-ray speckle-tracking. Only two images need…

### Applied Antineutrino Physics 2018 Proceedings. (arXiv:1911.06834v1 [hep-ex])

Proceedings for the 14th installment of Applied Antineutrino Physics (AAP) workshop series.

### Multireference electron correlation methods: Journeys along potential energy surfaces. (arXiv:1911.06836v1 [physics.chem-ph])

Multireference electron correlation methods describe static and dynamical electron correlation in a balanced way, and therefore, can yield accurate and predictive results even when single-reference methods or multiconfigurational self-consistent field (MCSCF) theory fails. One of their most prominent applications in quantum chemistry is the exploration of potential energy surfaces (PES). This includes the optimization of…

### Transfer Learning of fMRI Dynamics. (arXiv:1911.06813v1 [eess.IV])

As a mental disorder progresses, it may affect brain structure, but brain function expressed in brain dynamics is affected much earlier. Capturing the moment when brain dynamics express the disorder is crucial for early diagnosis. The traditional approach to this problem via training classifiers either proceeds from handcrafted features or requires large datasets to combat…

### Data-efficient Co-Adaptation of Morphology and Behaviour with Deep Reinforcement Learning. (arXiv:1911.06832v1 [cs.LG])

Humans and animals are capable of quickly learning new behaviours to solve new tasks. Yet, we often forget that they also rely on a highly specialized morphology that co-adapted with motor control throughout thousands of years. Although compelling, the idea of co-adapting morphology and behaviours in robots is often unfeasible because of the long manufacturing…

### Performance assessment of the 2$\gamma$ positronium imaging with the total-body PET scanners. (arXiv:1911.06841v1 [physics.ins-det])

In living organisms the positron-electron annihilation (occurring during the PET imaging) proceeds in about 30% via creation of a metastable ortho-positronium atom. In the tissue, due to the pick-off and conversion processes, over 98% of ortho-positronia annihilate into two 511~keV photons. In this article we assess the feasibility for reconstruction of the mean ortho-positronium lifetime…

### Scintillation light production, propagation, and detection in the 4-ton dual-phase LAr-TPC demonstrator (data analysis and simulations). (arXiv:1911.06874v1 [physics.ins-det])

The Deep Underground Neutrino Experiment (DUNE) Far Detector (FD) will be formed by four 10-kton Liquid Argon (LAr) Time Projection Chambers (TPC) using both single and dual-phase technology. The dual-phase technology foreseen the charge amplification in the gas phase before the signal collection and is following a staged approach to demonstrate its feasibility at the…

### Improved Exploration through Latent Trajectory Optimization in Deep Deterministic Policy Gradient. (arXiv:1911.06833v1 [cs.LG])

Model-free reinforcement learning algorithms such as Deep Deterministic Policy Gradient (DDPG) often require additional exploration strategies, especially if the actor is of deterministic nature. This work evaluates the use of model-based trajectory optimization methods used for exploration in Deep Deterministic Policy Gradient when trained on a latent image embedding. In addition, an extension of DDPG…

### Dynamic Modeling and Equilibria in Fair Decision Making. (arXiv:1911.06837v1 [cs.LG])

Recent studies on fairness in automated decision making systems have both investigated the potential future impact of these decisions on the population at large, and emphasized that imposing ”typical” fairness constraints such as demographic parity or equality of opportunity does not guarantee a benefit to disadvantaged groups. However, these previous studies have focused on either…

### QC-Automator: Deep Learning-based Automated Quality Control for Diffusion MR Images. (arXiv:1911.06816v1 [eess.IV])

Quality assessment of diffusion MRI (dMRI) data is essential prior to any analysis, so that appropriate pre-processing can be used to improve data quality and ensure that the presence of MRI artifacts do not affect the results of subsequent image analysis. Manual quality assessment of the data is subjective, possibly error-prone, and infeasible, especially considering…

### Ambipolar perovskite light electrochemical cell for transparent display devices. (arXiv:1911.06875v1 [physics.app-ph])

Perovskite light-emitting diodes (PeLEDs) have recently attracted great research luminescence at room temperature in interest for their narrow emissions and solution processability. Remarkable progress has been achieved PeLEDs in recent years. Here we present the new configuration of ambipolar transparent perovskite light emitting device. The combination of voltage induced p-i-n formation and ionically doped carbon…

### Empirical Study of Off-Policy Policy Evaluation for Reinforcement Learning. (arXiv:1911.06854v1 [cs.LG])

Off-policy policy evaluation (OPE) is the problem of estimating the online performance of a policy using only pre-collected historical data generated by another policy. Given the increasing interest in deploying learning-based methods for safety-critical applications, many recent OPE methods have recently been proposed. Due to disparate experimental conditions from recent literature, the relative performance of…

### Review of Quantitative Systems Pharmacological Modeling in Thrombosis. (arXiv:1911.07018v1 [q-bio.TO])

Hemostasis and thrombosis are often thought as two sides of the same clotting mechanism whereas hemostasis is a natural protective mechanism to prevent bleeding and thrombosis is a blood clot abnormally formulated inside a blood vessel, blocking the normal blood flow. The evidence to date suggests that at least arterial thrombosis results from the same…

### Microsimulation of Energy and Flow Effects from Optimal Automated Driving in Mixed Traffic. (arXiv:1911.06818v1 [eess.SY])

This paper studies the energy and traffic impact of a proposed Cooperative and Anticipative Cruise Controller in a PTV VISSIM microsimulation environment. We dissect our controller into two parts: 1. the anticipative mode, more immediately beneficial when automated vehicle fleet penetration is low, and 2. the connected mode, beneficial in coordinated platooning scenarios and high…

### Semiparametric Estimation of Correlated Random Coefficient Models without Instrumental Variables. (arXiv:1911.06857v1 [econ.EM])

We study a linear random coefficient model where slope parameters may be correlated with some continuous covariates. Such a model specification may occur in empirical research, for instance, when quantifying the effect of a continuous treatment observed at two time periods. We show one can carry identification and estimation without instruments. We propose a semiparametric…

### Handwritten and Machine printed OCR for Geez Numbers Using Artificial Neural Network. (arXiv:1911.06845v1 [cs.CV])

Researches have been done on Ethiopic scripts. However studies excluded the Geez numbers from the studies because of different reasons. This paper presents offline handwritten and machine printed Geez number recognition using feed forward back propagation artificial neural network. On this study, different Geez image characters were collected from google image search and three persons…

### Evaluation of techniques for predicting seizure Build up. (arXiv:1911.07081v1 [eess.SP])

The analysis of electrophysiological signal of scalp: EEG (electroencephalography), MEG (magnetoencephalography) and depth (intracerebral EEG) IEEG is a way to delimit epileptogenic zone (EZ). These epileptic signals present two different activities (oscillations and spikes) which can be overlapped in the time frequency plane. Automatic recognition of epileptic seizure occurrence needs several preprocessing steps. In this…

### Bayesian Ordinal Quantile Regression with a Partially Collapsed Gibbs Sampler. (arXiv:1911.07099v1 [stat.ME])

Unlike standard linear regression, quantile regression captures the relationship between covariates and the conditional response distribution as a whole, rather than only the relationship between covariates and the expected value of the conditional response. However, while there are well-established quantile regression methods for continuous variables and some forms of discrete data, there is no widely…

### A Sparse Bayesian Deep Learning Approach for Identification of Cascaded Tanks Benchmark. (arXiv:1911.06847v1 [eess.SY])

Nonlinear system identification is important with a wide range of applications. The typical approaches for nonlinear system identification include Volterra series models, nonlinear autoregressive with exogenous inputs models, block-structured models, state-space models and neural network models. Among them, neural networks (NN) is an important black-box method thanks to its universal approximation capability and less dependency…

### Training DNA Perceptrons via Fractional Coding. (arXiv:1911.07110v1 [cs.ET])

This paper describes a novel approach to synthesize molecular reactions to train a perceptron, i.e., a single-layered neural network, with sigmoidal activation function. The approach is based on fractional coding where a variable is represented by two molecules. The synergy between fractional coding in molecular computing and stochastic logic implementations in electronic computing is key…

### Deep Learning with Persistent Homology for Orbital Angular Momentum (OAM) Decoding. (arXiv:1911.06858v1 [eess.SP])

Orbital angular momentum (OAM)-encoding has recently emerged as an effective approach for increasing the channel capacity of free-space optical communications. In this paper, OAM-based decoding is formulated as a supervised classification problem. To maintain lower error rate in presence of severe atmospheric turbulence, a new approach that combines effective machine learning tools from persistent homology…

### Adaptive Multi-scale Detection of Acoustic Events. (arXiv:1911.06878v1 [eess.AS])

The goal of acoustic (or sound) events detection (AED or SED) is to predict the temporal position of target events in given audio segments. This task plays a significant role in safety monitoring, acoustic early warning and other scenarios. However, the deficiency of data and diversity of acoustic event sources make the AED task a…

### Imitation in the Imitation Game. (arXiv:1911.06893v1 [cs.CY])

We discuss the objectives of automation equipped with non-trivial decision making, or creating artificial intelligence, in the financial markets and provide a possible alternative. Intelligence might be an unintended consequence of curiosity left to roam free, best exemplified by a frolicking infant. For this unintentional yet welcome aftereffect to set in a foundational list of…

### Thesis Deployment Optimization of IoT Devices through Attack Graph Analysis. (arXiv:1911.06811v1 [cs.CR])

The Internet of things (IoT) has become an integral part of our life at both work and home. However, these IoT devices are prone to vulnerability exploits due to their low cost, low resources, the diversity of vendors, and proprietary firmware. Moreover, short range communication protocols (e.g., Bluetooth or ZigBee) open additional opportunities for the…

### Application of Principal Component Analysis in Chinese Sovereign Bond Market and Principal Component-Based Fixed Income Immunization. (arXiv:1911.07288v1 [q-fin.ST])

This paper analyses the Chinese Sovereign bond yield to find out the principal factors affecting the term structure of interest rate changes. We apply Principal Component Analysis (PCA) on our data consisting of the Chinese Sovereign bond from January 2002 till May 2018 with the different yield to maturity. Then we will discuss the multi-factor…

### Adaptive Learning Guidance System (ALGS). (arXiv:1911.06812v1 [cs.CY])

This poster presents the conceptual framework of the Adaptive Learning Guidance System ALGS. The system aims to propose a model for adaptive learning environments where two major concerns arising from past studies are being addressed; the marginal role of the teacher, and the need for a big data approach. Most past studies marginalized the teacher…

### Mathematical Modeling of Systemic Risk in Financial Networks: Managing Default Contagion and Fire Sales. (arXiv:1911.07313v1 [q-fin.RM])

As impressively shown by the financial crisis in 2007/08, contagion effects in financial networks harbor a great threat for the stability of the entire system. Without sufficient capital requirements for banks and other financial institutions, shocks that are locally confined at first can spread through the entire system and be significantly amplified by various contagion…

### Transfer Learning of fMRI Dynamics. (arXiv:1911.06813v1 [eess.IV])

As a mental disorder progresses, it may affect brain structure, but brain function expressed in brain dynamics is affected much earlier. Capturing the moment when brain dynamics express the disorder is crucial for early diagnosis. The traditional approach to this problem via training classifiers either proceeds from handcrafted features or requires large datasets to combat…

### Bayesian Filtering for Multi-period Mean-Variance Portfolio Selection. (arXiv:1911.07526v1 [q-fin.PM])

For a long investment time horizon, it is preferable to rebalance the portfolio weights at intermediate times. This necessitates a multi-period market model in which portfolio optimization is usually done through dynamic programming. However, this assumes a known distribution for the parameters of the financial time series. We consider the situation where this distribution is…

### Causal inference with recurrent data via inverse probability treatment weighting method (IPTW). (arXiv:1911.06868v1 [stat.ME])

Propensity score methods are increasingly being used to reduce estimation bias of treatment effects for observational studies. Previous research has shown that propensity score methods consistently estimate the marginal hazard ratio for time to event data. However, recurrent data frequently arise in the biomedical literature and there is a paucity of research into the use…

### Experiments in Detecting Persuasion Techniques in the News. (arXiv:1911.06815v1 [cs.CL])

Many recent political events, like the 2016 US Presidential elections or the 2018 Brazilian elections have raised the attention of institutions and of the general public on the role of Internet and social media in influencing the outcome of these events. We argue that a safe democracy is one in which citizens have tools to…

### The Laplace transform of the integrated Volterra Wishart process. (arXiv:1911.07719v1 [math.PR])

We establish an explicit expression for the conditional Laplace transform of the integrated Volterra Wishart process in terms of a certain resolvent of the covariance function. The core ingredient is the derivation of the conditional Laplace transform of general Gaussian processes in terms of Fredholm’s determinant and resolvent. Furthermore , we link the characteristic exponents…

### Analysis of the light production and propagation in the 4-tonne dual-phase demonstrator. (arXiv:1911.06880v1 [physics.ins-det])

The Deep Underground Neutrino Experiment (DUNE) is a leading-edge experiment designed to perform neutrino science and proton decay searches. In particular, the far detector will consist of four 10-kton Liquid Argon (LAr) Time Projection Chambers using both single and dual-phase technologies. The latter provides charge amplification in the gaseous phase. In order to optimize these…

### A Bootstrap-based Inference Framework for Testing Similarity of Paired Networks. (arXiv:1911.06869v1 [stat.ME])

We live in an interconnected world where network valued data arises in many domains, and, fittingly, statistical network analysis has emerged as an active area in the literature. However, the topic of inference in networks has received relatively less attention. In this work, we consider the paired network inference problem where one is given two…

### QC-Automator: Deep Learning-based Automated Quality Control for Diffusion MR Images. (arXiv:1911.06816v1 [eess.IV])

Quality assessment of diffusion MRI (dMRI) data is essential prior to any analysis, so that appropriate pre-processing can be used to improve data quality and ensure that the presence of MRI artifacts do not affect the results of subsequent image analysis. Manual quality assessment of the data is subjective, possibly error-prone, and infeasible, especially considering…

### Using the Multirhodotron as an Advanced Rhodotron. (arXiv:1911.06887v1 [physics.acc-ph])

This article assesses the use of a new type of electron accelerator, the Multirhodotron, for four new purposes that cannot be implemented using Rhodotrons and linacs. This study awards some arguments about possible replacement of nuclear reactors by electron accelerators in process of producing of medical isotopes on a global scale, about new possible electron…

### Explanatory Masks for Neural Network Interpretability. (arXiv:1911.06876v1 [cs.LG])

Neural network interpretability is a vital component for applications across a wide variety of domains. In such cases it is often useful to analyze a network which has already been trained for its specific purpose. In this work, we develop a method to produce explanation masks for pre-trained networks. The mask localizes the most important…

### Opportunities for artificial intelligence in advancing precision medicine. (arXiv:1911.07125v1 [cs.AI])

Machine learning (ML), deep learning (DL), and artificial intelligence (AI) are of increasing importance in biomedicine. The goal of this work is to show progress in ML in digital health, to exemplify future needs and trends, and to identify any essential prerequisites of AI and ML for precision health. High-throughput technologies are delivering growing volumes…

### Role-Oriented Code Generation in an Engine for Solving Hyperbolic PDE Systems. (arXiv:1911.06817v1 [cs.MS])

The development of a high performance PDE solver requires the combined expertise of interdisciplinary teams w.r.t. application domain, numerical scheme and low-level optimization. In this paper, we present how the ExaHyPE engine facilitates the collaboration of such teams by isolating three roles — application, algorithms, and optimization expert — thus allowing team members to focus…

### Adaptive Leader-Follower Formation Control and Obstacle Avoidance via Deep Reinforcement Learning. (arXiv:1911.06882v1 [cs.RO])

We propose a deep reinforcement learning (DRL) methodology for the tracking, obstacle avoidance, and formation control of nonholonomic robots. By separating vision-based control into a perception module and a controller module, we can train a DRL agent without sophisticated physics or 3D modeling. In addition, the modular framework averts daunting retrains of an image-to-action end-to-end…

### A unified breaking onset criterion for surface gravity water waves in arbitrary depth. (arXiv:1911.06896v1 [physics.flu-dyn])

We investigate the validity and robustness of the Barthelemy et al. (2018) breaking wave onset prediction framework for surface gravity water waves in arbitrary water depth, including shallow water breaking over varying bathymetry. We show that the Barthelemy et al. (2018) breaking onset criterion, which they validated for deep and intermediate water depths, also segregates…

### The implications of Labour’s plan to scrap Key Stage 2 tests for Progress 8 and secondary school accountability in England. (arXiv:1911.06884v1 [stat.AP])

In England, Progress 8 is the Conservative government’s headline secondary school performance and accountability measure. Progress 8 attempts to measure the average academic progress pupils make in each school between their KS2 tests and their GCSE Attainment 8 examinations. The Labour opposition recently announced they would scrap the KS2 tests were they to be elected.…

### Fixed-horizon Active Hypothesis Testing. (arXiv:1911.06912v1 [eess.SY])

Two active hypothesis testing problems are formulated. In these problems, the agent can perform a fixed number of experiments and then decide on one of the hypotheses. The agent is also allowed to declare its experiments inconclusive if needed. The first problem is an asymmetric formulation in which the the objective is to minimize the…

### Quantum Computing at the Frontiers of Biological Sciences. (arXiv:1911.07127v1 [quant-ph])

The search for meaningful structure in biological data has relied on cutting-edge advances in computational technology and data science methods. However, challenges arise as we push the limits of scale and complexity in biological problems. Innovation in massively parallel, classical computing hardware and algorithms continues to address many of these challenges, but there is a…

### High-numerical-aperture and long-working-distance objectives for single-atom experiments. (arXiv:1911.06929v1 [physics.optics])

We present two long-working-distance objective lenses with numerical apertures (NA) of 0.29 and 0.4 for single-atom experiments. The objective lenses are assembled entirely by the commercial on-catalog $\Phi$1” singlets. Both the objectives are capable to correct the spherical aberrations due to the standard flat vacuum glass windows with various thickness. The working distances of NA$=0.29$…

### Variance partitioning in multilevel models for count data. (arXiv:1911.06888v1 [stat.ME])

A first step when fitting multilevel models to continuous responses is to explore the degree of clustering in the data. Researchers fit variance-component models and then report the proportion of variation in the response that is due to systematic differences between clusters or equally the response correlation between units within a cluster. These statistics are…

### Granular Motor State Monitoring of Free Living Parkinson’s Disease Patients via Deep Learning. (arXiv:1911.06913v1 [stat.AP])

Parkinson’s disease (PD) is the second most common neurodegenerative disease worldwide and affects around 1% of the (60+ years old) elderly population in industrial nations. More than 80% of PD patients suffer from motor symptoms, which could be well addressed if a personalized medication schedule and dosage could be administered to them. However, such personalized…

### Temperate and chronic virus competition leads to low lysogen frequency. (arXiv:1911.07233v1 [q-bio.PE])

The canonical bacteriophage is obligately lytic: the virus infects a bacterium and hijacks cell functions to produce large numbers of new viruses which burst from the cell. These viruses are well-studied, but there exist a wide range of coexisting virus lifestyles that are less understood. Temperate viruses exhibit both a lytic cycle and a latent…

### Characterizing Magnetized Plasmas with Dynamic Mode Decomposition. (arXiv:1911.06938v1 [physics.plasm-ph])

Accurate and efficient plasma models are essential to understand and control experimental devices. Existing magnetohydrodynamic or kinetic models are nonlinear, computationally intensive, and can be difficult to interpret, while often only approximating the true dynamics. In this work, data-driven techniques recently developed in the field of fluid dynamics are leveraged to develop interpretable reduced-order models…

### Topological based classification using graph convolutional networks. (arXiv:1911.06892v1 [cs.SI])

In colored graphs, node classes are often associated with either their neighbors class or with information not incorporated in the graph associated with each node. We here propose that node classes are also associated with topological features of the nodes. We use this association to improve Graph machine learning in general and specifically, Graph Convolutional…

### 3D Conditional Generative Adversarial Networks to enable large-scale seismic image enhancement. (arXiv:1911.06932v1 [eess.IV])

We propose GAN-based image enhancement models for frequency enhancement of 2D and 3D seismic images. Seismic imagery is used to understand and characterize the Earth’s subsurface for energy exploration. Because these images often suffer from resolution limitations and noise contamination, our proposed method performs large-scale seismic volume frequency enhancement and denoising. The enhanced images reduce…

### Modelling of Bad Biomass Invasion of a Food Chain Ecosystem with Optimal Control. (arXiv:1911.07322v1 [q-bio.PE])

In this paper we provide a model to describe the dynamics of the species of the ecosystem after it has been raided by a bad competing specie. The competing specie invades the native plants for nutrition, carbon dioxide and space. This affects the population of the native species of the ecosystem. The effect of the…

### Upward Overshooting in Turbulent Compressible Convection. I.Effects of the relative stability parameter, the Prandtl number, and the P\’eclet number. (arXiv:1911.06942v1 [astro-ph.SR])

In this paper, we investigate the upward overshooting by three-dimensional numerical simulations. We find that the above convectively stable zone can be partitioned into three layers: the thermal adjustment layer (mixing both entropy and material), the turbulent dissipation layer (mixing material but not entropy), and the thermal dissipation layer (mixing neither entropy nor material). The…

### The Creation and Validation of Load Time Series for Synthetic Electric Power Systems. (arXiv:1911.06934v1 [eess.SY])

Synthetic power systems that imitate functional and statistical characteristics of the actual grid have been developed to promote researchers’ access to public system models. Developing time series to represent different operating conditions of these synthetic systems will expand the potential of synthetic power systems applications. This paper proposes a methodology to create synthetic time series…

### Spatial Resolution of Local Field Potential Signals in Macaque V4. (arXiv:1911.07388v1 [q-bio.NC])

A main challenge for the development of cortical visual prostheses is to spatially localize individual spots of light, called phosphenes, by assigning appropriate stimulating parameters to implanted electrodes. Imitating the natural responses to phosphene-like stimuli at different positions can help in designing a systematic procedure to determine these parameters. The key characteristic of such a…

### On Space-spectrum Uncertainty Analysis for Coded Aperture Systems. (arXiv:1911.06956v1 [eess.IV])

We introduce and analyze the concept of space-spectrum uncertainty for certain commonly-used designs for spectrally programmable cameras. Our key finding states that, it is impossible to simultaneously capture high-resolution spatial images while programming the spectrum at high resolution. This phenomenon arises due to a Fourier relationship between the aperture used for obtaining spectrum and its…

### Characterization of Intact Eukaryotic Cells with Subcellular Spatial Resolution by Photothermal-Induced Resonance Infrared Spectroscopy and Imaging. (arXiv:1911.07560v1 [q-bio.QM])

Photothermal-Induced Resonance (PTIR) spectroscopy and imaging with infrared light has seen increasing application in molecular spectroscopy of biological samples. The appeal of the technique lies in its capability to provide information about IR light absorption at a spatial resolution better than allowed by light diffraction, typically below 100 nm. In the present work we test…

### Microsimulation of Energy and Flow Effects from Optimal Automated Driving in Mixed Traffic. (arXiv:1911.06818v1 [eess.SY])

This paper studies the energy and traffic impact of a proposed Cooperative and Anticipative Cruise Controller in a PTV VISSIM microsimulation environment. We dissect our controller into two parts: 1. the anticipative mode, more immediately beneficial when automated vehicle fleet penetration is low, and 2. the connected mode, beneficial in coordinated platooning scenarios and high…

### Model Hierarchy for the Shape Optimization of a Microchannel Cooling System. (arXiv:1911.06819v1 [math.OC])

We model a microchannel cooling system and consider the optimization of its shape by means of shape calculus. A three-dimensional model covering all relevant physical effects and three reduced models are introduced. The latter are derived via a homogenization of the geometry in 3D and a transformation of the three-dimensional models to two dimensions. A…

### Backward propagation of chaos. (arXiv:1911.06835v1 [math.PR])

This paper develops a theory of propagation of chaos for a system of weakly interacting particles whose terminal configuration is fixed as opposed to the initial configuration as customary. Such systems are modeled by backward stochastic differential equations. Under standard assumptions on the coefficients of the equations, we prove propagation of chaos results and quantitative…

### Robust Model Predictive Control via System Level Synthesis. (arXiv:1911.06842v1 [math.OC])

In this paper, we consider the robust model predictive control (MPC) problem of a linear time-variant (LTV) system with both norm-bounded disturbances and model uncertainty. In robust MPC, a series of constrained optimal control problems (OCPs) are solved. Solving these robust OCPs is challenging since disturbances can cause deviation from the predicted states and model…

### An Optimal Transport approach for the Schr\”odinger bridge problem and convergence of Sinkhorn algorithm. (arXiv:1911.06850v1 [math.PR])

This paper exploit the equivalence between the Schr\”odinger Bridge problem and the entropy penalized optimal transport in order to find a different approach to the duality, in the spirit of optimal transport. This approach results in a priori estimates which are consistent in the limit when the regularization parameter goes to zero. In particular, we…

### On the discretness of states accessible via right-angled paths in hyperbolic space. (arXiv:1911.06853v1 [math.GT])

We consider the control problem where, given an orthonormal tangent frame in the hyperbolic plane or three dimensional hyperbolic space, one is allowed to transport the frame a fixed distance $r > 0$ along the geodesic in direction of the first vector, or rotate it in place a right angle. We characterize the values of…

### Microsimulation of Energy and Flow Effects from Optimal Automated Driving in Mixed Traffic. (arXiv:1911.06818v1 [eess.SY])

This paper studies the energy and traffic impact of a proposed Cooperative and Anticipative Cruise Controller in a PTV VISSIM microsimulation environment. We dissect our controller into two parts: 1. the anticipative mode, more immediately beneficial when automated vehicle fleet penetration is low, and 2. the connected mode, beneficial in coordinated platooning scenarios and high…

### Model Hierarchy for the Shape Optimization of a Microchannel Cooling System. (arXiv:1911.06819v1 [math.OC])

We model a microchannel cooling system and consider the optimization of its shape by means of shape calculus. A three-dimensional model covering all relevant physical effects and three reduced models are introduced. The latter are derived via a homogenization of the geometry in 3D and a transformation of the three-dimensional models to two dimensions. A…

### Data-efficient Co-Adaptation of Morphology and Behaviour with Deep Reinforcement Learning. (arXiv:1911.06832v1 [cs.LG])

Humans and animals are capable of quickly learning new behaviours to solve new tasks. Yet, we often forget that they also rely on a highly specialized morphology that co-adapted with motor control throughout thousands of years. Although compelling, the idea of co-adapting morphology and behaviours in robots is often unfeasible because of the long manufacturing…

### Improved Exploration through Latent Trajectory Optimization in Deep Deterministic Policy Gradient. (arXiv:1911.06833v1 [cs.LG])

Model-free reinforcement learning algorithms such as Deep Deterministic Policy Gradient (DDPG) often require additional exploration strategies, especially if the actor is of deterministic nature. This work evaluates the use of model-based trajectory optimization methods used for exploration in Deep Deterministic Policy Gradient when trained on a latent image embedding. In addition, an extension of DDPG…

### Dynamic Modeling and Equilibria in Fair Decision Making. (arXiv:1911.06837v1 [cs.LG])

Recent studies on fairness in automated decision making systems have both investigated the potential future impact of these decisions on the population at large, and emphasized that imposing ”typical” fairness constraints such as demographic parity or equality of opportunity does not guarantee a benefit to disadvantaged groups. However, these previous studies have focused on either…

### Review and new concepts for neutron-capture measurements of astrophysical interest. (arXiv:1911.06972v1 [physics.ins-det])

The idea of slow-neutron capture nucleosynthesis formulated in 1957 triggered a tremendous experimental effort in different laboratories worldwide to measure the relevant nuclear physics input quantities, namely ($n,\gamma$) cross sections over the stellar temperature range (from few eV up to several hundred keV) for most of the isotopes involved from Fe up to Bi. A…

### The Directed Dominating Set problem studied by cavity method: Warning propagation and population dynamics. (arXiv:1911.06974v1 [physics.soc-ph])

The minimal dominating set for a digraph(directed graph)is a prototypical hard combinatorial optimization problem. In a previous paper, we studied this problem using the cavity method. Although we found a solution for a given graph that gives very good estimate of the minimal dominating size, we further developed the one step replica symmetry breaking theory…

### Bonding in light-induced vortices: benzene in a high-frequency circular polarized laser. (arXiv:1911.06976v1 [physics.chem-ph])

The electronic structure of benzene in the presence of a high-intensity high-frequency circularly polarized laser supports a middle-of-the-ring electron localization. Here, the laser polarization coincides with the ring plane of benzene. The high-frequency oscillating electric field creates circular currents centered at each atom with a circle radius equal to the maximum field amplitude of the…

### Post- versus pre-resonance characteristics of axially excited chiral sculptured thin films. (arXiv:1911.06984v1 [physics.optics])

Axially excited chiral sculptured thin films (STFs) are shown to exhibit the circular Bragg phenomenon in the pre-resonant (long-wavelength) regime but not in some parts of the post-resonant (short-wavelength) regime. Chiral STFs act as very good polarization-independent reflectors in the vicinity of material resonances in the latter regime.

### The Second Laws for Quantum and Nano-scale Heat Engines. (arXiv:1911.07003v1 [quant-ph])

The second law in thermodynamics dictates which state transformations are statistically unlikely or effectively forbidden. However, the statistical formulation of the second law assumes the asymptotic regime, where a system of an asymptotically large number of particles interacts with the thermal baths. In addition, standard thermodynamics relies on mean values of thermodynamic quantities and admits…

### Optimal perturbations and transition energy thresholds in boundary layer shear flows. (arXiv:1911.07019v1 [physics.flu-dyn])

Subcritical transition to turbulence in spatially developing boundary layer flows can be triggered efficiently by finite amplitude perturbations. In this work, we employ adjoint-based optimization to identify optimal initial perturbations in the Blasius boundary layer, culminating in the computation of the critical energy threshold for subcritical transition and the associated fully localized critical optimum in…

### Full distribution of first exit times in the narrow escape problem. (arXiv:1911.07637v1 [cond-mat.stat-mech])

In the scenario of the narrow escape problem (NEP) a particle diffuses in a finite container and eventually leaves it through a small “escape window” in the otherwise impermeable boundary, once it arrives to this window and over-passes an entropic barrier at the entrance to it. This generic problem is mathematically identical to that of…

### Query Complexity of Bayesian Private Learning. (arXiv:1911.06903v1 [cs.LG])

We study the query complexity of Bayesian Private Learning: a learner wishes to locate a random target within an interval by submitting queries, in the presence of an adversary who observes all of her queries but not the responses. How many queries are necessary and sufficient in order for the learner to accurately estimate the…

### Coupling Matrix Manifolds and Their Applications in Optimal Transport. (arXiv:1911.06905v1 [cs.LG])

Optimal transport (OT) is a powerful tool for measuring the distance between two defined probability distributions. In this paper, we develop a new manifold named the coupling matrix manifold (CMM), where each point on CMM can be regarded as the transportation plan of the OT problem. We firstly explore the Riemannian geometry of CMM with…

### Deep Discriminative Fine-Tuning for Cancer Type Classification. (arXiv:1911.07654v1 [q-bio.GN])

Determining the primary site of origin for metastatic tumors is one of the open problems in cancer care because the efficacy of treatment often depends on the cancer tissue of origin. Classification methods that can leverage tumor genomic data and predict the site of origin are therefore of great value. Because tumor DNA point mutation…

### Fixed-horizon Active Hypothesis Testing. (arXiv:1911.06912v1 [eess.SY])

Two active hypothesis testing problems are formulated. In these problems, the agent can perform a fixed number of experiments and then decide on one of the hypotheses. The agent is also allowed to declare its experiments inconclusive if needed. The first problem is an asymmetric formulation in which the the objective is to minimize the…

### How data, synapses and neurons interact with each other: a variational principle marrying gradient ascent and message passing. (arXiv:1911.07662v1 [stat.ML])

Unsupervised learning requiring only raw data is not only a fundamental function of the cerebral cortex, but also a foundation for a next generation of artificial neural networks. However, a unified theoretical framework to treat sensory inputs, synapses and neural activity together is still lacking. The computational obstacle originates from the discrete nature of synapses,…

### Comparison of screening for methicillin-resistant Staphylococcus aureus (MRSA) at hospital admission and discharge. (arXiv:1911.07711v1 [q-bio.PE])

Methicillin-resistant Staphylococcus aureus (MRSA) is a significant contributor to the growing concern of antibiotic resistant bacteria, especially given its stubborn persistence in hospitals and other health care facility settings. In combination with this characteristic of S. aureus (colloquially referred to as staph), MRSA presents an additional barrier to treatment and is now believed to have…

### Granular Motor State Monitoring of Free Living Parkinson’s Disease Patients via Deep Learning. (arXiv:1911.06913v1 [stat.AP])

Parkinson’s disease (PD) is the second most common neurodegenerative disease worldwide and affects around 1% of the (60+ years old) elderly population in industrial nations. More than 80% of PD patients suffer from motor symptoms, which could be well addressed if a personalized medication schedule and dosage could be administered to them. However, such personalized…

### Benanza: Automatic uBenchmark Generation to Compute “Lower-bound” Latency and Inform Optimizations of Deep Learning Models on GPUs. (arXiv:1911.06922v1 [cs.LG])

As Deep Learning (DL) models have been increasingly used in latency-sensitive applications, there has been a growing interest in improving their response time. An important venue for such improvement is to profile the execution of these models and characterize their performance to identify possible optimization opportunities. However, the current profiling tools lack the highly desired…

### Generalized Maximum Causal Entropy for Inverse Reinforcement Learning. (arXiv:1911.06928v1 [cs.LG])

We consider the problem of learning from demonstrated trajectories with inverse reinforcement learning (IRL). Motivated by a limitation of the classical maximum entropy model in capturing the structure of the network of states, we propose an IRL model based on a generalized version of the causal entropy maximization problem, which allows us to generate a…

### Semiparametric Estimation of Correlated Random Coefficient Models without Instrumental Variables. (arXiv:1911.06857v1 [econ.EM])

We study a linear random coefficient model where slope parameters may be correlated with some continuous covariates. Such a model specification may occur in empirical research, for instance, when quantifying the effect of a continuous treatment observed at two time periods. We show one can carry identification and estimation without instruments. We propose a semiparametric…

### Innovation and Strategic Network Formation. (arXiv:1911.06872v1 [econ.TH])

We study a model of innovation with a large number of firms that create new technologies by combining several discrete ideas. These ideas can be acquired by private investment or via social learning. Firms face a choice between secrecy, which protects existing intellectual property, and openness, which facilitates social learning. These decisions determine interaction rates…

### Biophysical characterization of DNA origami nanostructures reveals inaccessibility to intercalation binding sites. (arXiv:1911.07022v1 [physics.bio-ph])

Intercalation of drug molecules into synthetic DNA nanostructures formed through self-assembled origami has been postulated as a valuable future method for targeted drug delivery. This is due to the excellent biocompatibility of synthetic DNA nanostructures, and high potential for flexible programmability including facile drug release into or near to target cells. Such favourable properties may…

### Period-doubling bifurcation of dissipative-soliton-resonance pulses in a passively mode-locked fiber laser. (arXiv:1911.07026v1 [physics.optics])

We report on the experimental observation of period-doubling bifurcation of dissipative-soliton-resonance (DSR) pulses in a fiber laser passively mode-locked by using the nonlinear optical loop mirror. Increasing the pump power of the fiber laser, we show that temporally a stable, uniform DSR pulse train could be transformed into a period-doubling state, exhibiting two sets of…

### Emergence of Self-Sustained Oscillations for SIRS Model on Random Networks. (arXiv:1911.07031v1 [physics.soc-ph])

We study the phase transition from the persistence phase to the extinction phase for the SIRS (susceptible/ infected/ refractory/ susceptible) model of diseases spreading on random networks. By studying temporal evolution and synchronization parameter of this model on random networks, we find that, this model on random networks, shows a synchronization phase in a narrow…

### Critical Threshold For SIRS Model on Small World Networks. (arXiv:1911.07035v1 [physics.soc-ph])

We study the phase transition from the persistence phase to the extinction phase for the SIRS (susceptible/ infected/ refractory/ susceptible) model of diseases spreading on small world network. We show the effects of all the parameters associated with this model on small world network and we create the full phase space. The results we obtained…

### Quantum Enhanced Imaging of Non-Uniform Refractive Profiles. (arXiv:1911.07039v1 [physics.optics])

In this work quantum metrology techniques are applied to the imaging of objects with a non-uniform refractive spatial profile. A sensible improvement on the classical accuracy is shown to be found when the “Twin Beam State” (TWB) is used. In particular exploiting the multimode spatial correlation, naturally produced in the Parametric Down Conversion (PDC) process,…

### Photonic-chip assisted correlative light and electron microscopy. (arXiv:1911.07055v1 [physics.optics])

Correlative light-electron microscopy (CLEM) unifies the versatility of light microscopy (LM) with the high resolution of electron microscopy (EM), allowing one to zoom into the complex organization of cells. Most CLEM techniques use ultrathin sections, and thus lack the 3D-EM structural information, and focusing on a very restricted field of view. Here, we introduce photonic…

### Handwritten and Machine printed OCR for Geez Numbers Using Artificial Neural Network. (arXiv:1911.06845v1 [cs.CV])

Researches have been done on Ethiopic scripts. However studies excluded the Geez numbers from the studies because of different reasons. This paper presents offline handwritten and machine printed Geez number recognition using feed forward back propagation artificial neural network. On this study, different Geez image characters were collected from google image search and three persons…

### Wave maps and constant curvature surfaces: singularities and bifurcations. (arXiv:1911.06856v1 [math.DG])

Wave maps (or Lorentzian-harmonic maps) from a $1+1$-dimensional Lorentz space into the $2$-sphere are associated to constant negative Gaussian curvature surfaces in Euclidean 3-space via the Gauss map, which is harmonic with respect to the metric induced by the second fundamental form. We give a method for constructing germs of Lorentzian-harmonic maps from their $k$-jets…

### A Sparse Bayesian Deep Learning Approach for Identification of Cascaded Tanks Benchmark. (arXiv:1911.06847v1 [eess.SY])

Nonlinear system identification is important with a wide range of applications. The typical approaches for nonlinear system identification include Volterra series models, nonlinear autoregressive with exogenous inputs models, block-structured models, state-space models and neural network models. Among them, neural networks (NN) is an important black-box method thanks to its universal approximation capability and less dependency…

### Deep Learning with Persistent Homology for Orbital Angular Momentum (OAM) Decoding. (arXiv:1911.06858v1 [eess.SP])

Orbital angular momentum (OAM)-encoding has recently emerged as an effective approach for increasing the channel capacity of free-space optical communications. In this paper, OAM-based decoding is formulated as a supervised classification problem. To maintain lower error rate in presence of severe atmospheric turbulence, a new approach that combines effective machine learning tools from persistent homology…

### Assigning Medical Codes at the Encounter Level by Paying Attention to Documents. (arXiv:1911.06848v1 [cs.CL])

The vast majority of research in computer assisted medical coding focuses on coding at the document level, but a substantial proportion of medical coding in the real world involves coding at the level of clinical encounters, each of which is typically represented by a potentially large set of documents. We introduce encounter-level document attention networks,…

### The Mori fan of the Dolgachev-Nikulin-Voisin family in genus $2$. (arXiv:1911.06862v1 [math.AG])

In this paper we study the Mori fan of the Dolgachev-Nikulin-Voisin family in degree $2$ as well as the associated secondary fan. The main result is an enumeration of all maximal dimensional cones of the two fans.

### Curriculum Self-Paced Learning for Cross-Domain Object Detection. (arXiv:1911.06849v1 [cs.CV])

Training (source) domain bias affects state-of-the-art object detectors, such as Faster R-CNN, when applied to new (target) domains. To alleviate this problem, researchers proposed various domain adaptation methods to improve object detection results in the cross-domain setting, e.g. by translating images with ground-truth labels from the source domain to the target domain using Cycle-GAN or…

### Some applications of Fibonacci and Lucas numbers. (arXiv:1911.06863v1 [math.RA])

In this paper, we provide new applications of Fibonacci and Lucas numbers. In some circumstances, we find algebraic structures on some sets defined with these numbers, we generalize Fibonacci and Lucas numbers by using an arbitrary binary relation over the real fields instead of addition of the real numbers and we give properties of the…

### Empirical Study of Off-Policy Policy Evaluation for Reinforcement Learning. (arXiv:1911.06854v1 [cs.LG])

Off-policy policy evaluation (OPE) is the problem of estimating the online performance of a policy using only pre-collected historical data generated by another policy. Given the increasing interest in deploying learning-based methods for safety-critical applications, many recent OPE methods have recently been proposed. Due to disparate experimental conditions from recent literature, the relative performance of…

### Stochastic decompositions in bivariate risk and queueing models with mutual assistance. (arXiv:1911.06867v1 [math.PR])

We consider two bivariate models with two-way interactions in context of risk and queueing theory. The two entities interact with each other by providing assistance but otherwise evolve independently. We focus on certain random quantities underlying the joint survival probability and the joint stationary workload, and show that these admit stochastic decomposition. Each one can…

### Deep Learning with Persistent Homology for Orbital Angular Momentum (OAM) Decoding. (arXiv:1911.06858v1 [eess.SP])

Orbital angular momentum (OAM)-encoding has recently emerged as an effective approach for increasing the channel capacity of free-space optical communications. In this paper, OAM-based decoding is formulated as a supervised classification problem. To maintain lower error rate in presence of severe atmospheric turbulence, a new approach that combines effective machine learning tools from persistent homology…

### Expected difference of order statistics in terms of hazard rate. (arXiv:1911.06870v1 [math.PR])

If the hazard rate $ \frac{ F'(x) }{ 1-F(x) } $ is increasing (in $x$), then $ \mathbb E\, ( X_{n:n} – X_{n-1:n} ) $ is decreasing (in $n$), and moreover, completely monotone.

### Low Frequency Asymptotics and Electro-Magneto-Statics for Time-Harmonic Maxwell’s Equations in Exterior Weak Lipschitz Domains with Mixed Boundary Conditions. (arXiv:1911.06871v1 [math.AP])

We prove that the time-harmonic solutions to Maxwell’s equations in a 3D exterior domain converge to a certain static solution as the frequency tends to zero. We work in weighted Sobolev spaces and construct new compactly supported replacements for Dirichlet-Neumann fields. Moreover, we even show convergence in operator norm.

### Spectral stability of smooth solitary waves for the Degasperis-Procesi Equation. (arXiv:1911.06885v1 [math.AP])

The Degasperis-Procesi equation is an approximating model of shallow-water wave propagating mainly in one direction to the Euler equations. Such a model equation is analogous to the Camassa-Holm approximation of the two-dimensional incompressible and irrotational Euler equations with the same asymptotic accuracy, and is integrable with the bi-Hamiltonian structure. In the present study, we establish…

### Learning Behavioral Representations from Wearable Sensors. (arXiv:1911.06959v1 [cs.LG])

The ubiquity of mobile devices and wearable sensors offers unprecedented opportunities for continuous collection of multimodal physiological data. Such data enables temporal characterization of an individual’s behaviors, which can provide unique insights into her physical and psychological health. Understanding the relation between different behaviors/activities and personality traits such as stress or work performance can help…

### Integrality of Linearizations of Polynomials over Binary Variables using Additional Monomials. (arXiv:1911.06894v1 [cs.DM])

Polynomial optimization problems over binary variables can be expressed as integer programs using a linearization with extra monomials in addition to those arising in the given polynomial. We characterize when such a linearization yields an integral relaxation polytope, generalizing work by Del Pia and Khajavirad (SIAM Journal on Optimization, 2018). We also present an algorithm…

### Optimal Storage Control for Dynamic Pricing. (arXiv:1911.06963v1 [eess.SY])

Renewable energy brings huge uncertainties to the power system, which challenges the traditional power system operation with limited flexible resources. One promising solution is to introduce dynamic pricing to more consumers, which, if designed properly, could enable an active demand side. To further exploit flexibility, in this work, we seek to advice the consumers an…

### On Hermite-Hadamard type inequalities for harmonical $h$-convex interval-valued functions. (arXiv:1911.06900v1 [math.GM])

We introduce and investigate the concept of harmonical $h$-convexity for interval-valued functions. Under this new concept, we prove some new Hermite-Hadamard type inequalities for the interval Riemann integral.

### Music theme recognition using CNN and self-attention. (arXiv:1911.07041v1 [cs.SD])

We present an efficient architecture to detect mood/themes in music tracks on autotagging-moodtheme subset of the MTG-Jamendo dataset. Our approach consists of two blocks, a CNN block based on MobileNetV2 architecture and a self-attention block from Transformer architecture to capture long term temporal characteristics. We show that our proposed model produces a significant improvement over…

### Query Complexity of Bayesian Private Learning. (arXiv:1911.06903v1 [cs.LG])

We study the query complexity of Bayesian Private Learning: a learner wishes to locate a random target within an interval by submitting queries, in the presence of an adversary who observes all of her queries but not the responses. How many queries are necessary and sufficient in order for the learner to accurately estimate the…

### Automatic Annotation of Hip Anatomy in Fluoroscopy for Robust and Efficient 2D/3D Registration. (arXiv:1911.07042v1 [cs.CV])

Fluoroscopy is the standard imaging modality used to guide hip surgery and is therefore a natural sensor for computer-assisted navigation. In order to efficiently solve the complex registration problems presented during navigation, human-assisted annotations of the intraoperative image are typically required. This manual initialization interferes with the surgical workflow and diminishes any advantages gained from…

### Strategy-Stealing is Non-Constructive. (arXiv:1911.06907v1 [cs.DS])

In many combinatorial games, one can prove that the first player wins under best play using a simple but non-constructive argument called strategy-stealing. This work is about the complexity behind these proofs: how hard is it to actually find a winning move in a game, when you know by strategy-stealing that one exists? We prove…

### N-HANS: Introducing the Augsburg Neuro-Holistic Audio-eNhancement System. (arXiv:1911.07062v1 [cs.SD])

N-HANS is a Python toolkit for in-the-wild audio enhancement, including speech, music, and general audio denoising, separation, and selective noise or source suppression. The functionalities are realised based on two neural network models sharing the same architecture, but trained separately. The models are comprised of stacks of residual blocks, each conditioned on additional speech or…

### ResUNet++: An Advanced Architecture for Medical Image Segmentation. (arXiv:1911.07067v1 [eess.IV])

Accurate computer-aided polyp detection and segmentation during colonoscopy examinations can help endoscopists resect abnormal tissue and thereby decrease chances of polyps growing into cancer. Towards developing a fully automated model for pixel-wise polyp segmentation, we propose ResUNet++, which is an improved ResUNet architecture for colonoscopic image segmentation. Our experimental evaluations show that the suggested architecture…

### NeuMMU: Architectural Support for Efficient Address Translations in Neural Processing Units. (arXiv:1911.06859v1 [cs.AR])

To satisfy the compute and memory demands of deep neural networks, neural processing units (NPUs) are widely being utilized for accelerating deep learning algorithms. Similar to how GPUs have evolved from a slave device into a mainstream processor architecture, it is likely that NPUs will become first class citizens in this fast-evolving heterogeneous architecture space.…

### Large-Scale Parallel Matching of Social Network Profiles. (arXiv:1911.06861v1 [cs.SI])

A profile matching algorithm takes as input a user profile of one social network and returns, if existing, the profile of the same person in another social network. Such methods have immediate applications in Internet marketing, search, security, and a number of other domains, which is why this topic saw a recent surge in popularity.…

### Multi-attention Networks for Temporal Localization of Video-level Labels. (arXiv:1911.06866v1 [cs.CV])

Temporal localization remains an important challenge in video understanding. In this work, we present our solution to the 3rd YouTube-8M Video Understanding Challenge organized by Google Research. Participants were required to build a segment-level classifier using a large-scale training data set with noisy video-level labels and a relatively small-scale validation data set with accurate segment-level…

### Explanatory Masks for Neural Network Interpretability. (arXiv:1911.06876v1 [cs.LG])

Neural network interpretability is a vital component for applications across a wide variety of domains. In such cases it is often useful to analyze a network which has already been trained for its specific purpose. In this work, we develop a method to produce explanation masks for pre-trained networks. The mask localizes the most important…

### Causal Inference Under Approximate Neighborhood Interference. (arXiv:1911.07085v1 [econ.EM])

This paper studies causal inference in randomized experiments under network interference. Most existing models of interference posit that treatments assigned to alters only affect the ego’s response through a low-dimensional exposure mapping, which only depends on units within some known network radius around the ego. We propose a substantially weaker “approximate neighborhood interference” (ANI) assumption,…

### Robust Reserve Pricing in Auctions under Mean Constraints. (arXiv:1911.07103v1 [econ.TH])

We study a seller who sets a reserve price in a second price auction with uncertainty over the joint distribution of bidders’ valuations. The seller only knows the mean of the marginal distribution of each bidder’s valuation and the range, and an adversarial nature chooses the worst-case distribution within this ambiguity set. We use a…

### Inference in Models of Discrete Choice with Social Interactions Using Network Data. (arXiv:1911.07106v1 [econ.EM])

This paper studies inference in models of discrete choice with social interactions when the data consists of a single large network. We provide theoretical justification for the use of spatial and network HAC variance estimators in applied work, the latter constructed by using network path distance in place of spatial distance. Toward this end, we…

### An Analysis Framework for Metric Voting based on LP Duality. (arXiv:1911.07162v1 [cs.GT])

Distortion-based analysis has established itself as a fruitful framework for comparing voting mechanisms. m voters and n candidates are jointly embedded in an (unknown) metric space, and the voters submit rankings of candidates by non-decreasing distance from themselves. Based on the submitted rankings, the social choice rule chooses a winning candidate; the quality of the…

### Optimal Search and Awareness Expansion. (arXiv:1911.07773v1 [econ.TH])

This paper introduces a search problem where a consumer has to first become aware of an alternative, before being able to search it. Initially, the consumer is aware of only a few alternatives. During search, the consumer sequentially decides between searching alternatives he is already aware of and expanding awareness to discover more products. I…

### Optimal Incentive Contract with Endogenous Monitoring Technology. (arXiv:1810.11471v5 [econ.TH] UPDATED)

Recent technology advances have enabled firms to flexibly process and analyze sophisticated employee performance data at a reduced and yet significant cost. We develop a theory of optimal incentive contracting where the monitoring technology that governs the above procedure is part of the designer’s strategic planning. In otherwise standard principal-agent models with moral hazard, we…

### Optimal Search and Awareness Expansion. (arXiv:1911.07773v1 [econ.TH])

This paper introduces a search problem where a consumer has to first become aware of an alternative, before being able to search it. Initially, the consumer is aware of only a few alternatives. During search, the consumer sequentially decides between searching alternatives he is already aware of and expanding awareness to discover more products. I…

### Diffusion Approximations for Expert Opinions in a Financial Market with Gaussian Drift. (arXiv:1807.00568v3 [q-fin.PM] UPDATED)

This paper investigates a financial market where returns depend on an unobservable Gaussian drift process. While the observation of returns yields information about the underlying drift, we also incorporate discrete-time expert opinions as an external source of information. For estimating the hidden drift it is crucial to consider the conditional distribution of the drift given…

### Optimal Incentive Contract with Endogenous Monitoring Technology. (arXiv:1810.11471v5 [econ.TH] UPDATED)

Recent technology advances have enabled firms to flexibly process and analyze sophisticated employee performance data at a reduced and yet significant cost. We develop a theory of optimal incentive contracting where the monitoring technology that governs the above procedure is part of the designer’s strategic planning. In otherwise standard principal-agent models with moral hazard, we…

### Can Deep Learning Predict Risky Retail Investors? A Case Study in Financial Risk Behavior Forecasting. (arXiv:1812.06175v3 [q-fin.RM] UPDATED)

The paper examines the potential of deep learning to support decisions in financial risk management. We develop a deep learning model for predicting whether individual spread traders secure profits from future trades. This task embodies typical modeling challenges faced in risk and behavior forecasting. Conventional machine learning requires data that is representative of the feature-target…

### The Impact of Renewable Energy Forecasts on Intraday Electricity Prices. (arXiv:1903.09641v2 [econ.GN] UPDATED)

In this paper we study the impact of errors in wind and solar power forecasts on intraday electricity prices. We develop a novel econometric model which is based on day-ahead wholesale auction curves data and errors in wind and solar power forecasts. The model shifts day-ahead supply curves to calculate intraday prices. We apply our…

### Enhancing Time Series Momentum Strategies Using Deep Neural Networks. (arXiv:1904.04912v2 [stat.ML] UPDATED)

While time series momentum is a well-studied phenomenon in finance, common strategies require the explicit definition of both a trend estimator and a position sizing rule. In this paper, we introduce Deep Momentum Networks — a hybrid approach which injects deep learning based trading rules into the volatility scaling framework of time series momentum. The…

### Renewal reward perspective on linear switching diffusion systems. (arXiv:1911.07746v1 [q-bio.SC])

In many biological systems, the movement of individual agents is commonly characterized as having multiple qualitatively distinct behaviors that arise from various biophysical states. This is true for vesicles in intracellular transport, micro-organisms like bacteria, or animals moving within and responding to their environment. For example, in cells the movement of vesicles, organelles and other…

### Biological Value of Centaurea damascena: Minireview. (arXiv:1911.07788v1 [q-bio.QM])

The family Asteraceae include large number of Centaurea species which have been applied in folk medicine. One of the family Asteraceae members is the Centaurea damascena which authentically been tested for its antibacterial activity. The aim of the study was to discuss antibacterial activities of essential oil composition and methanolic extract of the same plant…

### Law of the Minimum Paradoxes. (arXiv:0907.1965v4 [q-bio.PE] UPDATED)

The “Law of the Minimum” states that growth is controlled by the scarcest resource (limiting factor). This concept was originally applied to plant or crop growth (Justus von Liebig, 1840) and quantitatively supported by many experiments. Some generalizations based on more complicated “dose-response” curves were proposed. Violations of this law in natural and experimental ecosystems…

### Infinite graphs in systematic biology, with an application to the species problem. (arXiv:1201.2869v7 [q-bio.PE] UPDATED)

We argue that C. Darwin and more recently W. Hennig worked at times under the simplifying assumption of an eternal biosphere. So motivated, we explicitly consider the consequences which follow mathematically from this assumption, and the infinite graphs it leads to. This assumption admits certain clusters of organisms which have some ideal theoretical properties of…

### Sleep-like slow oscillations improve visual classification through synaptic homeostasis and memory association in a thalamo-cortical model. (arXiv:1810.10498v5 [q-bio.NC] UPDATED)

The occurrence of sleep passed through the evolutionary sieve and is widespread in animal species. Sleep is known to be beneficial to cognitive and mnemonic tasks, while chronic sleep deprivation is detrimental. Despite the importance of the phenomenon, a complete understanding of its functions and underlying mechanisms is still lacking. In this paper, we show…

### Spectral Dynamic Causal Modelling of Resting-State fMRI: Relating Effective Brain Connectivity in the Default Mode Network to Genetics. (arXiv:1901.09975v7 [q-bio.NC] UPDATED)

We conduct an imaging genetics study to explore how effective brain connectivity in the default mode network (DMN) may be related to genetics within the context of Alzheimer’s disease and mild cognitive impairment. We develop an analysis of longitudinal resting-state functional magnetic resonance imaging (rs-fMRI) and genetic data obtained from a sample of 111 subjects…

### Inverse Reinforcement Learning with Missing Data. (arXiv:1911.06930v1 [cs.LG])

We consider the problem of recovering an expert’s reward function with inverse reinforcement learning (IRL) when there are missing/incomplete state-action pairs or observations in the demonstrated trajectories. This issue of missing trajectory data or information occurs in many situations, e.g., GPS signals from vehicles moving on a road network are intermittent. In this paper, we…

### Fairness With Minimal Harm: A Pareto-Optimal Approach For Healthcare. (arXiv:1911.06935v1 [cs.LG])

Common fairness definitions in machine learning focus on balancing notions of disparity and utility. In this work, we study fairness in the context of risk disparity among sub-populations. We are interested in learning models that minimize performance discrepancies across sensitive groups without causing unnecessary harm. This is relevant to high-stakes domains such as healthcare, where…

### $DC^2$: A Divide-and-conquer Algorithm for Large-scale Kernel Learning with Application to Clustering. (arXiv:1911.06944v1 [cs.LG])

Divide-and-conquer is a general strategy to deal with large scale problems. It is typically applied to generate ensemble instances, which potentially limits the problem size it can handle. Additionally, the data are often divided by random sampling which may be suboptimal. To address these concerns, we propose the $DC^2$ algorithm. Instead of ensemble instances, we…

### Marginal and Interactive Feature Screening of Ultra-high Dimensional Feature Spaces with Multivariate Response. (arXiv:1911.06955v1 [stat.ME])

When the number of features exponentially outnumbers the number of samples, feature screening plays a pivotal role in reducing the dimension of the feature space and developing models based on such data. While most extant feature screening approaches are only applicable to data having univariate response, we propose a new method (GenCorr) that admits a…

### Learning Behavioral Representations from Wearable Sensors. (arXiv:1911.06959v1 [cs.LG])

The ubiquity of mobile devices and wearable sensors offers unprecedented opportunities for continuous collection of multimodal physiological data. Such data enables temporal characterization of an individual’s behaviors, which can provide unique insights into her physical and psychological health. Understanding the relation between different behaviors/activities and personality traits such as stress or work performance can help…

### Inductive Relation Prediction on Knowledge Graphs. (arXiv:1911.06962v1 [cs.LG])

Inferring missing edges in multi-relational knowledge graphs is a fundamental task in statistical relational learning. However, previous work has largely focused on the transductive relation prediction problem, where missing edges must be predicted for a single, fixed graph. In contrast, many real-world situations require relation prediction on dynamic or previously unseen knowledge graphs (e.g., for…

### Strengths of near-threshold optical Feshbach resonances. (arXiv:1911.07063v1 [physics.atom-ph])

Optical Feshbach resonances allow one to control cold atomic scattering, produce ultracold molecules and study atomic interactions via photoassociation spectroscopy. Here we give practical analytic expressions for the strength parameter, the optical length, of Feshbach resonances due to near-threshold bound states of an excited molecular state dominated by either a resonant-dipole or van der Waals…

### Multilayer plasmonic photonic structures embedding photochromic molecules or optical gain molecules. (arXiv:1911.07070v1 [physics.optics])

We design photonic structures embedding different functional molecular systems of photochromic switching and lasing. We study the light absorption of two photochromic molecules and of 4,4′-bis[(N-carbazole)styryl]biphenyl (BSB-Cz) with density functional theory. For the photochromic diarylethene we derivate the refractive index with Kramers-Kronig relations and we design multilayer photonic structures alternating diarylethene with either poly vinyl…

### Electric field assisted alignment of monoatomic carbon chains. (arXiv:1911.07071v1 [physics.atm-clus])

We stabilize monoatomic carbon chains in water by attaching them to gold nanoparticles (NPs) by means of the laser ablation process. Resulting nanoobjects represent pairs of NPs connected by multiple straight carbon chains of several nanometer lengths. If NPs at the opposite ends of a chain differ in size, the structure acquires a dipole moment…

### Omnidirectional perfect acoustic cloak realized by homogeneous materials. (arXiv:1911.07073v1 [physics.app-ph])

Acoustic cloaks derived by coordinate transformation have opened up a new field of considerable interest in the last two decades. However, since perfect omnidirectional acoustic cloak relies on inhomogeneous and anisotropic materials that posses extreme values in certain regions, this cloak was deemed impossible to be attained even with metamaterials. Recently, our group was competent…

### Science Challenges in Low Temperature Plasma Science and Engineering: Enabling a Future Based on Electricity through Non-Equilibrium Plasma Chemistry. (arXiv:1911.07076v1 [physics.plasm-ph])

The science and technology of Low Temperature Plasmas (LTPs) harbor dynamic and versatile methods of converting the potential energy of electricity to chemical reactivity, thereby enabling the Future Based on Renewable Electricity (FBRE). Research on LTPs connects fields as diverse as engineering, plasma physics, biology and medicine, and so LTPs embody the definition of convergent…

### On equilibrium equations and their perturbations using three different variational formulations of nonlinear electroelastostatics. (arXiv:1911.07090v1 [physics.class-ph])

We derive the equations of nonlinear electroelastostatics using three different variational formulations involving the deformation function and an independent field variable representing the electric character – considering either one of the electric field $\mathbb{E}$, electric displacement $\mathbb{D}$, or electric polarization $\mathbb{P}$. The first variation of the energy functional results in the set of Euler-Lagrange partial…

### Kvasir-SEG: A Segmented Polyp Dataset. (arXiv:1911.07069v1 [eess.IV])

Pixel-wise image segmentation is a highly demanding task in medical-image analysis. In practice, it is difficult to find annotated medical images with corresponding segmentation masks. In this paper, we present Kvasir-SEG: an open-access dataset of gastrointestinal polyp images and corresponding segmentation masks, manually annotated by a medical doctor and then verified by an experienced gastroenterologist.…

### Integration of stationary wavelet transform on a dynamic partial reconfiguration: case study separating preictal gamma oscillations from transitory activities for early build up epileptic seizure. (arXiv:1911.07078v1 [eess.SP])

To define the neural networks responsible of the epileptic seizure, we had to study the electrophysiological signal in a proper way. The early recognition of the seizure build up could also be defined through the time space mapping of the preictal gamma oscillations. The electrophysiological signals present three types of wave: oscillations, spikes, and a…

### Evaluation of techniques for predicting seizure Build up. (arXiv:1911.07081v1 [eess.SP])

The analysis of electrophysiological signal of scalp: EEG (electroencephalography), MEG (magnetoencephalography) and depth (intracerebral EEG) IEEG is a way to delimit epileptogenic zone (EZ). These epileptic signals present two different activities (oscillations and spikes) which can be overlapped in the time frequency plane. Automatic recognition of epileptic seizure occurrence needs several preprocessing steps. In this…

### Liver Steatosis Segmentation with Deep Learning Methods. (arXiv:1911.07088v1 [eess.IV])

Liver steatosis is known as the abnormal accumulation of lipids within cells. An accurate quantification of steatosis area within the liver histopathological microscopy images plays an important role in liver disease diagnosis and trans-plantation assessment. Such a quantification analysis often requires a precise steatosis segmentation that is challenging due to abundant presence of highly overlapped…

### VOICe: A Sound Event Detection Dataset For Generalizable Domain Adaptation. (arXiv:1911.07098v1 [cs.SD])

The performance of sound event detection methods can significantly degrade when they are used in unseen conditions (e.g. recording devices, ambient noise). Domain adaptation is a promising way to tackle this problem. In this paper, we present VOICe, the first dataset for the development and evaluation of domain adaptation methods for sound event detection. VOICe…

### Homogenization of oblique boundary value problems. (arXiv:1911.06909v1 [math.AP])

We consider a nonlinear Neumann problem, with periodic oscillation in the elliptic operator and on the boundary condition. Our focus is on problems posed in half-spaces, but with general normal directions that may not be parallel to the directions of periodicity. As the frequency of the oscillation grows, quantitative homogenization results are derived. When the…

### Particle Swarm and EDAs. (arXiv:1911.07112v1 [cs.NE])

The Particle Swarm Optimization (PSO) algorithm is developed for solving the Schaffer F6 function in fewer than 4000 function evaluations on a total of 30 runs. Four variations of the Full Model of Particle Swarm Optimization (PSO) algorithms are presented which consist of combinations of Ring and Star topologies with Synchronous and Asynchronous updates. The…

### The quadratic Wasserstein metric for inverse data matching. (arXiv:1911.06911v1 [math.NA])

This work characterizes, analytically and numerically, two major effects of the quadratic Wasserstein ($W_2$) distance as the measure of data discrepancy in computational solutions of inverse problems. First, we show, in the infinite-dimensional setup, that the $W_2$ distance has a smoothing effect on the inversion process, making it robust against high-frequency noise in the data…

### Fixed-horizon Active Hypothesis Testing. (arXiv:1911.06912v1 [eess.SY])

Two active hypothesis testing problems are formulated. In these problems, the agent can perform a fixed number of experiments and then decide on one of the hypotheses. The agent is also allowed to declare its experiments inconclusive if needed. The first problem is an asymmetric formulation in which the the objective is to minimize the…

### Local minimizers with unbounded vorticity for the $2$d Ginzburg-Landau functional. (arXiv:1911.06914v1 [math.AP])

A central focus of Ginzburg-Landau theory is the understanding and characterization of vortex configurations. On a bounded domain $\Omega\subseteq \mathbb{R}^2,$ global minimizers, and critical states in general, of the corresponding energy functional have been studied thoroughly in the limit $\epsilon\to 0,$ where $\epsilon>0$ is the inverse of the Ginzburg-Landau parameter. The presence of an applied…

### Regularity and asymptotic behavior of laminar flames in higher dimensions. (arXiv:1911.06916v1 [math.AP])

We study a parabolic free boundary problem, arising from a model for the propagation of equi-diffusional premixed flames with high activation energy. If an initial data is compactly supported, then the solution vanishes in a finite time, called the extinction time. In this paper, we give a quantitative estimate on the flatness of the free…

### A Fully Stochastic Second-Order Trust Region Method. (arXiv:1911.06920v1 [math.OC])

A stochastic second-order trust region method is proposed, which can be viewed as a second-order extension of the trust-region-ish (TRish) algorithm proposed by Curtis et al. (INFORMS J. Optim. 1(3) 200-220, 2019). In each iteration, a search direction is computed by (approximately) solving a trust region subproblem defined by stochastic gradient and Hessian estimates. The…

### Exploring Configurations for Multi-user Communication in Virtual Reality. (arXiv:1911.06877v1 [cs.HC])

Virtual Reality (VR) enables users to collaborate while exploring scenarios not realizable in the physical world. We propose CollabVR, a distributed multi-user collaboration environment, to explore how digital content improves expression and understanding of ideas among groups. To achieve this, we designed and examined three possible configurations for participants and shared manipulable objects. In configuration…

### Adaptive Multi-scale Detection of Acoustic Events. (arXiv:1911.06878v1 [eess.AS])

The goal of acoustic (or sound) events detection (AED or SED) is to predict the temporal position of target events in given audio segments. This task plays a significant role in safety monitoring, acoustic early warning and other scenarios. However, the deficiency of data and diversity of acoustic event sources make the AED task a…

### Separating Local & Shuffled Differential Privacy via Histograms. (arXiv:1911.06879v1 [cs.CR])

Recent work in differential privacy has highlighted the shuffled model as a promising avenue to compute accurate statistics while keeping raw data in users’ hands. We present a protocol in this model that estimates histograms with error independent of the domain size. This implies an arbitrarily large gap in sample complexity between the shuffled and…

### Adaptive Leader-Follower Formation Control and Obstacle Avoidance via Deep Reinforcement Learning. (arXiv:1911.06882v1 [cs.RO])

We propose a deep reinforcement learning (DRL) methodology for the tracking, obstacle avoidance, and formation control of nonholonomic robots. By separating vision-based control into a perception module and a controller module, we can train a DRL agent without sophisticated physics or 3D modeling. In addition, the modular framework averts daunting retrains of an image-to-action end-to-end…

### New Query Lower Bounds for Submodular Function MInimization. (arXiv:1911.06889v1 [cs.DS])

We consider submodular function minimization in the oracle model: given black-box access to a submodular set function $f:2^{[n]}\rightarrow \mathbb{R}$, find an element of $\arg\min_S \{f(S)\}$ using as few queries to $f(\cdot)$ as possible. State-of-the-art algorithms succeed with $\tilde{O}(n^2)$ queries [LeeSW15], yet the best-known lower bound has never been improved beyond $n$ [Harvey08]. We provide a…

### The Augmented Synthetic Control Method. (arXiv:1811.04170v2 [stat.ME] UPDATED)

The synthetic control method (SCM) is a popular approach for estimating the impact of a treatment on a single unit in panel data settings. The “synthetic control” is a weighted average of control units that balances the treated unit’s pre-treatment outcomes as closely as possible. A critical feature of the original proposal is to use…

### Solving the Reswitching Paradox in the Sraffian Theory of Capital. (arXiv:1907.01189v4 [econ.TH] UPDATED)

The possibility of re-switching of techniques in Piero Sraffa’s intersectoral model, namely the returning capital-intensive techniques with monotonic changes in the profit rate, is traditionally considered as a paradox putting at stake the viability of the neoclassical theory of production. It is argued here that this phenomenon can be rationalized within the neoclassical paradigm. Sectoral…

### Analysing Global Fixed Income Markets with Tensors. (arXiv:1908.02101v3 [q-fin.PM] UPDATED)

Global fixed income returns span across multiple maturities and economies, that is, they naturally reside on multi-dimensional data structures referred to as tensors. In contrast to standard “flat-view” multivariate models that are agnostic to data structure and only describe linear pairwise relationships, we introduce a tensor-valued approach to model the global risks shared by multiple…

### Credit risk with asymmetric information and a switching default threshold. (arXiv:1910.14413v2 [q-fin.PR] UPDATED)

We investigate the impact of available information on the estimation of the default probability within a generalized structural model for credit risk. The traditional structural model where default is triggered when the value of the firm’s asset falls below a constant threshold is extended by relaxing the assumption of a constant default threshold. The default…

### The Transport-based Mesh-free Method (TMM) and its applications in finance: a review. (arXiv:1911.00992v2 [math.AP] UPDATED)

We review a numerical technique, referred to as the Transport-based Mesh-free Method (TMM), and we discuss its applications to mathematical finance. We recently introduced this method from a numerical standpoint and investigated the accuracy of integration formulas based on the Monte-Carlo methodology: quantitative error bounds were discussed and, in this short note, we outline the…

### Robo-advising: Learning Investors’ Risk Preferences via Portfolio Choices. (arXiv:1911.02067v2 [q-fin.PM] UPDATED)

We introduce a reinforcement learning framework for retail robo-advising. The robo-advisor does not know the investor’s risk preference, but learns it over time by observing her portfolio choices in different market environments. We develop an exploration-exploitation algorithm which trades off costly solicitations of portfolio choices by the investor with autonomous trading decisions based on stale…

### Critical synchronization dynamics of the Kuramoto model on connectome and small world graphs. (arXiv:1903.00385v3 [cond-mat.dis-nn] UPDATED)

The hypothesis, that cortical dynamics operates near criticality also suggests, that it exhibits universal critical exponents which marks the Kuramoto equation, a fundamental model for synchronization, as a prime candidate for an underlying universal model. Here, we determined the synchronization behavior of this model by solving it numerically on a large, weighted human connectome network,…

### Augmenting expert detection of early coronary artery occlusion from 12 lead electrocardiograms using deep learning. (arXiv:1903.04421v4 [stat.AP] UPDATED)

Early diagnosis of acute coronary artery occlusion based on electrocardiogram (ECG) findings is essential for prompt delivery of primary percutaneous coronary intervention. Current ST elevation (STE) criteria are specific but insensitive. Consequently, it is likely that many patients are missing out on potentially life-saving treatment. Experts combining non-specific ECG changes with STE detect ischaemia with…

### Modeling Bottom-Up and Top-Down Attention with a Neurodynamic Model of V1. (arXiv:1904.02741v3 [q-bio.NC] UPDATED)

Previous studies suggested that lateral interactions of V1 cells are responsible, among other visual effects, of bottom-up visual attention (alternatively named visual salience or saliency). Our objective is to mimic these connections with a neurodynamic network of firing-rate neurons in order to predict visual attention. Early visual subcortical processes (i.e. retinal and thalamic) are functionally…

### Time-dependent product-form Poisson distributions for reaction networks with higher order complexes. (arXiv:1904.11583v2 [math.PR] UPDATED)

It is well known that stochastically modeled reaction networks that are complex balanced admit a stationary distribution that is a product of Poisson distributions. In this paper, we consider the following related question: supposing that the initial distribution of a stochastically modeled reaction network is a product of Poissons, under what conditions will the distribution…

### An “outside the box” solution for imbalanced data classification. (arXiv:1911.06965v1 [cs.LG])

A common problem of the real-world data sets is the class imbalance, which can significantly affect the classification abilities of classifiers. Numerous methods have been proposed to cope with this problem; however, even state-of-the-art methods offer a limited improvement (if any) for data sets with critically under-represented minority classes. For such problematic cases, an “outside…

### GIBBONFINDR: An R package for the detection and classification of acoustic signals. (arXiv:1906.02572v2 [eess.AS] UPDATED)

The recent improvements in recording technology, data storage and battery life have led to an increased interest in the use of passive acoustic monitoring for a variety of research questions. One of the main obstacles in implementing wide scale acoustic monitoring programs in terrestrial environments is the lack of user-friendly, open source programs for processing…

### Off-Policy Policy Gradient Algorithms by Constraining the State Distribution Shift. (arXiv:1911.06970v1 [cs.LG])

Off-policy deep reinforcement learning (RL) algorithms are incapable of learning solely from batch offline data without online interactions with the environment, due to the phenomenon known as \textit{extrapolation error}. This is often due to past data available in the replay buffer that may be quite different from the data distribution under the current policy. We…

### A Story of Two Streams: Reinforcement Learning Models from Human Behavior and Neuropsychiatry. (arXiv:1906.11286v3 [cs.LG] UPDATED)

Drawing an inspiration from behavioral studies of human decision making, we propose here a more general and flexible parametric framework for reinforcement learning that extends standard Q-learning to a two-stream model for processing positive and negative rewards, and allows to incorporate a wide range of reward-processing biases — an important component of human decision making…

### Parametric Graph-based Separable Transforms for Video Coding. (arXiv:1911.06981v1 [cs.MM])

In many video coding systems, separable transforms (such as two-dimensional DCT-2) have been used to code block residual signals obtained after prediction. This paper proposes a parametric approach to build graph-based separable transforms (GBSTs) for video coding. Specifically, a GBST is derived from a pair of line graphs, whose weights are determined based on two…

### Selective sampling for accelerating training of deep neural networks. (arXiv:1911.06996v1 [cs.LG])

We present a selective sampling method designed to accelerate the training of deep neural networks. To this end, we introduce a novel measurement, the minimal margin score (MMS), which measures the minimal amount of displacement an input should take until its predicted classification is switched. For multi-class linear classification, the MMS measure is a natural…

### A spatio-temporal multi-scale model for Geyer saturation point process: application to forest fire occurrences. (arXiv:1911.06999v1 [stat.AP])

Since most natural phenomena exhibit dependence at multiple scales (e.g. earthquake and forest fire occurrences), single-scale spatio-temporal Gibbs models are unrealistic in many applications. This motivates statisticians to construct the multi-scale generalizations of the classical Gibbs models and to develop new Gibbs point process models. In this paper, we extend the spatial multi-scale Geyer point…

### Spatiotemporal large-scale networks shaped by air mass movements. (arXiv:1911.07007v1 [stat.AP])

The movement of atmospheric air masses can be seen as a continuous and generally complex flow of gases and particles hovering over our planet. It can however be locally simplified by considering three-dimensional trajectories of air masses connecting distant areas of the globe during a given period of time. In this paper, we present a…

### General Regression Neural Networks, Radial Basis Function Neural Networks, Support Vector Machines, and Feedforward Neural Networks. (arXiv:1911.07115v1 [eess.SY])

The aim of this project is to develop a code to discover the optimal sigma value that maximum the F1 score and the optimal sigma value that maximizes the accuracy and to find out if they are the same. Four algorithms which can be used to solve this problem are: Genetic Regression Neural Networks (GRNNs),…

### Graph Topological Aspects of Granger Causal Network Learning. (arXiv:1911.07121v1 [math.ST])

We study Granger causality in the context of wide-sense stationary time series, where our focus is on the topological aspects of the underlying causality graph. We establish sufficient conditions (in particular, we develop the notion of a “strongly causal” graph topology) under which the true causality graph can be recovered via pairwise causality testing alone,…

### Extra Proximal-Gradient Inspired Non-local Network. (arXiv:1911.07144v1 [cs.CV])

Variational method and deep learning method are two mainstream powerful approaches to solve inverse problems in computer vision. To take advantages of advanced optimization algorithms and powerful representation ability of deep neural networks, we propose a novel deep network for image reconstruction. The architecture of this network is inspired by our proposed accelerated extra proximal…

### Subcarrier Assignment Schemes Based on Q-Learning in Wideband Cognitive Radio Networks. (arXiv:1911.07149v1 [eess.SP])

Subcarrier assignment is of crucial importance in wideband cognitive radio (CR) networks. In order to tackle the challenge that the traditional optimization-based methods are inappropriate in the dynamic spectrum access environment, an independent Q-learning-based scheme is proposed for the case that the secondary users (SUs) cannot exchange information while a collaborative Q-learning-based scheme is proposed…

### Exponentially slow motion of interface layers for the one-dimensional Allen-Cahn equation with nonlinear phase-dependent diffusivity. (arXiv:1911.06926v1 [math.AP])

This paper considers a one-dimensional generalized Allen-Cahn equation of the form \[ u_t = \varepsilon^2 (D(u)u_x)_x – f(u), \] where $\varepsilon>0$ is constant, $D=D(u)$ is a positive, uniformly bounded below diffusivity coefficient that depends on the phase field $u$ and $f(u)$ is a reaction function that can be derived from a double-well potential with minima…

### A class of quasilinear second order partial differential equations which describe spherical or pseudospherical surfaces. (arXiv:1911.06927v1 [math.DG])

Second order partial differential equations which describe spherical surfaces (ss) or pseudospherical surfaces (pss) are considered. These equations are equivalent to the structure equations of a metric with Gaussian curvature $K = 1$ or $K = -1$, respectively, and they can be seen as the compatibility condition of an associated su(2)-valued or sl(2, R)-valued linear…

### Thin subgroups isomorphic to Gromov–Piateski-Shapiro lattices. (arXiv:1911.06933v1 [math.GT])

In this paper we produce many examples of thin subgroups of special linear groups that are isomorphic to the fundamental groups of non-arithmetic hyperbolic manifolds. Specifically, we show that the non-arithmetic lattices in $\mathrm{SO}(n,1)$ constructed by Gromov and Piateski-Shapiro can be embedded into $\mathrm{SL}_{n+1}(\mathbb{R})$ so that their images are thin subgroups

### Classes of barren extensions. (arXiv:1911.06936v1 [math.LO])

Henle, Mathias, and Woodin proved that, provided that $\omega\rightarrow(\omega)^{\omega}$ holds in a model $M$ of ZF, then forcing with $([\omega]^{\omega},\subseteq^*)$ over $M$ adds no new sets of ordinals, thus earning the name a “barren” extension. Moreover, under an additional assumption, they proved that this generic extension preserves all strong partition cardinals. This forcing thus produces…

### Infinite energy equivariant harmonic maps, domination, and anti-de Sitter $3$-manifolds. (arXiv:1911.06937v1 [math.DG])

We generalize a well-known existence and uniqueness result for equivariant harmonic maps due to Corlette, Donaldson, and Labourie to a non-compact infinite energy setting and analyze the asymptotic behaviour of the harmonic maps. When the relevant representation is Fuchsian and has hyperbolic monodromy, our construction recovers a family of harmonic maps originally studied by Wolf.…

### The Overlap Gap Property and Approximate Message Passing Algorithms for $p$-spin models. (arXiv:1911.06943v1 [math.PR])

We consider the algorithmic problem of finding a near ground state (near optimal solution) of a $p$-spin model. We show that for a class of algorithms broadly defined as Approximate Message Passing (AMP), the presence of the Overlap Gap Property (OGP), appropriately defined, is a barrier. We conjecture that when $p\ge 4$ the model does…

### Topological based classification using graph convolutional networks. (arXiv:1911.06892v1 [cs.SI])

In colored graphs, node classes are often associated with either their neighbors class or with information not incorporated in the graph associated with each node. We here propose that node classes are also associated with topological features of the nodes. We use this association to improve Graph machine learning in general and specifically, Graph Convolutional…

### Imitation in the Imitation Game. (arXiv:1911.06893v1 [cs.CY])

We discuss the objectives of automation equipped with non-trivial decision making, or creating artificial intelligence, in the financial markets and provide a possible alternative. Intelligence might be an unintended consequence of curiosity left to roam free, best exemplified by a frolicking infant. For this unintentional yet welcome aftereffect to set in a foundational list of…

### Integrality of Linearizations of Polynomials over Binary Variables using Additional Monomials. (arXiv:1911.06894v1 [cs.DM])

Polynomial optimization problems over binary variables can be expressed as integer programs using a linearization with extra monomials in addition to those arising in the given polynomial. We characterize when such a linearization yields an integral relaxation polytope, generalizing work by Del Pia and Khajavirad (SIAM Journal on Optimization, 2018). We also present an algorithm…

### Delta-stepping SSSP: from Vertices and Edges to GraphBLAS Implementations. (arXiv:1911.06895v1 [cs.DS])

GraphBLAS is an interface for implementing graph algorithms. Algorithms implemented using the GraphBLAS interface are cast in terms of linear algebra-like operations. However, many graph algorithms are canonically described in terms of operations on vertices and/or edges. Despite the known duality between these two representations, the differences in the way algorithms are described using the…

### Functional Sequential Treatment Allocation. (arXiv:1812.09408v5 [econ.EM] UPDATED)

Consider a setting in which a policy maker assigns subjects to treatments, observing each outcome before the next subject arrives. Initially, it is unknown which treatment is best, but the sequential nature of the problem permits learning about the effectiveness of the treatments. While the multi-armed-bandit literature has shed much light on the situation when…

### The Impact of Renewable Energy Forecasts on Intraday Electricity Prices. (arXiv:1903.09641v2 [econ.GN] UPDATED)

In this paper we study the impact of errors in wind and solar power forecasts on intraday electricity prices. We develop a novel econometric model which is based on day-ahead wholesale auction curves data and errors in wind and solar power forecasts. The model shifts day-ahead supply curves to calculate intraday prices. We apply our…

### Solving the Reswitching Paradox in the Sraffian Theory of Capital. (arXiv:1907.01189v4 [econ.TH] UPDATED)

The possibility of re-switching of techniques in Piero Sraffa’s intersectoral model, namely the returning capital-intensive techniques with monotonic changes in the profit rate, is traditionally considered as a paradox putting at stake the viability of the neoclassical theory of production. It is argued here that this phenomenon can be rationalized within the neoclassical paradigm. Sectoral…

### Analysing Global Fixed Income Markets with Tensors. (arXiv:1908.02101v3 [q-fin.PM] UPDATED)

Global fixed income returns span across multiple maturities and economies, that is, they naturally reside on multi-dimensional data structures referred to as tensors. In contrast to standard “flat-view” multivariate models that are agnostic to data structure and only describe linear pairwise relationships, we introduce a tensor-valued approach to model the global risks shared by multiple…

### Time-consistent decisions and rational expectation equilibrium existence in DSGE models. (arXiv:1909.10915v3 [econ.TH] UPDATED)

We demonstrate that if all agents in an economy make time-consistent decisions and policies, then there exists no rational expectation equilibrium in a dynamic stochastic general equilibrium (DSGE) model, unless under very restrictive and special circumstances. Some time-consistent interest rate rules, such as Taylor rule, worsen the equilibrium non-existence issue in general circumstances. Monetary policy…

### Identification and inference in discrete choice models with imperfect information. (arXiv:1911.04529v2 [econ.EM] UPDATED)

In this paper we study identification and inference of preference parameters in a single-agent, static, discrete choice model where the decision maker may face attentional limits precluding her to exhaustively process information about the payoffs of the available alternatives. By leveraging on the notion of one-player Bayesian Correlated Equilibrium in Bergemann and Morris (2016), we…

### A Journalist, Editor, Survivor, Lawyer And Academic Weigh In On What’s Holding Back #MeToo In Australia

From non-disclosure agreements to the threat of defamation, survivors are silenced in Australia. View Entire Post › … https://www.buzzfeed.com/ginarushton/australia-metoo-stories-journalist-editor-survivor-lawyer from BuzzFeed News Gina Rushton

### 29 Astonishing Facts I’ve Learned From Watching David Attenborough’s “Seven Worlds, One Planet”

There’s a freaking snake that is LYING about being a spider! View Entire Post › … https://www.buzzfeed.com/sam_cleal/seven-worlds-one-planet-facts from BuzzFeed News Sam Cleal

### Predicting Drug-Drug Interactions from Molecular Structure Images. (arXiv:1911.06356v1 [cs.LG])

Predicting and discovering drug-drug interactions (DDIs) is an important problem and has been studied extensively both from medical and machine learning point of view. Almost all of the machine learning approaches have focused on text data or textual representation of the structural data of drugs. We present the first work that uses drug structure images…

### Solving Inverse Problems by Joint Posterior Maximization with a VAE Prior. (arXiv:1911.06379v1 [stat.ML])

In this paper we address the problem of solving ill-posed inverse problems in imaging where the prior is a neural generative model. Specifically we consider the decoupled case where the prior is trained once and can be reused for many different log-concave degradation models without retraining. Whereas previous MAP-based approaches to this problem lead to…

### On Data Enriched Logistic Regression. (arXiv:1911.06380v1 [stat.AP])

Biomedical researchers usually study the effects of certain exposures on disease risks among a well-defined population. To achieve this goal, the gold standard is to design a trial with an appropriate sample from that population. Due to the high cost of such trials, usually the sample size collected is limited and is not enough to…

### Estimation of dynamic networks for high-dimensional nonstationary time series. (arXiv:1911.06385v1 [math.ST])

This paper is concerned with the estimation of time-varying networks for high-dimensional nonstationary time series. Two types of dynamic behaviors are considered: structural breaks (i.e., abrupt change points) and smooth changes. To simultaneously handle these two types of time-varying features, a two-step approach is proposed: multiple change point locations are first identified based on comparing…

### Seq-U-Net: A One-Dimensional Causal U-Net for Efficient Sequence Modelling. (arXiv:1911.06393v1 [cs.LG])

Convolutional neural networks (CNNs) with dilated filters such as the Wavenet or the Temporal Convolutional Network (TCN) have shown good results in a variety of sequence modelling tasks. However, efficiently modelling long-term dependencies in these sequences is still challenging. Although the receptive field of these models grows exponentially with the number of layers, computing the…

### Mining News Events from Comparable News Corpora: A Multi-Attribute Proximity Network Modeling Approach. (arXiv:1911.06407v1 [cs.LG])

We present ProxiModel, a novel event mining framework for extracting high-quality structured event knowledge from large, redundant, and noisy news data sources. The proposed model differentiates itself from other approaches by modeling both the event correlation within each individual document as well as across the corpus. To facilitate this, we introduce the concept of a…

### Give me (un)certainty — An exploration of parameters that affect segmentation uncertainty. (arXiv:1911.06357v1 [eess.IV])

Segmentation tasks in medical imaging are inherently ambiguous: the boundary of a target structure is oftentimes unclear due to image quality and biological factors. As such, predicted segmentations from deep learning algorithms are inherently ambiguous. Additionally, “ground truth” segmentations performed by human annotators are in fact weak labels that further increase the uncertainty of outputs…

### Multiple Patients Behavior Detection in Real-time using mmWave Radar and Deep CNNs. (arXiv:1911.06363v1 [eess.SP])

To address potential gaps noted in patient monitoring in the hospital, a novel patient behavior detection system using mmWave radar and deep convolution neural network (CNN), which supports the simultaneous recognition of multiple patients’ behaviors in real-time, is proposed. In this study, we use an mmWave radar to track multiple patients and detect the scattering…

### Cavity-induced backscattering in a two-dimensional photonic topological system. (arXiv:1911.06323v1 [cond-mat.mes-hall])

The discovery of robust transport via topological states in electronic, photonic and phononic materials has deepened our understanding of wave propagation in condensed matter with prospects for critical applications of engineered metamaterials in communications, sensing, and controlling the environment. Topological protection of transmission has been demonstrated in the face of bent paths and on-site randomness…

### Numerical simulations of self-diffusiophoretic colloids at fluid interfaces. (arXiv:1911.06324v1 [cond-mat.soft])

The dynamics of active colloids is very sensitive to the presence of boundaries and interfaces which therefore can be used to control their motion. Here we analyze the dynamics of active colloids adsorbed at a fluid-fluid interface. By using a mesoscopic numerical approach which relies on an approximated numerical solution of the Navier-Stokes equation, we…

### Shape optimisation of stirring rods in mixing binary fluids. (arXiv:1911.06351v1 [physics.flu-dyn])

Mixing is an omnipresent process in a wide-range of industrial applications, which supports scientific efforts to devise techniques for optimising mixing processes under time and energy constraints. In this endeavor, we present a computational framework based on nonlinear direct-adjoint looping for the enhancement of mixing efficiency in a binary fluid system. The governing equations consist…

### Correcting for Model Changes in Statistical Post-Processing — An approach based on Response Theory. (arXiv:1911.06361v1 [physics.ao-ph])

For most statistical post-processing schemes used to correct weather forecasts, changes to the forecast model induce a considerable reforcasting effort. We present a new approach based on response theory to cope with slight model change. In this framework, the model change is seen as a perturbation of the original forecast model. The response theory allows…

### Non-linear neoclassical model for poloidal asymmetries in tokamak pedestals: diamagnetic and radial effects included. (arXiv:1911.06365v1 [physics.plasm-ph])

Stronger impurity density in-out poloidal asymmetries than predicted by the most comprehensive neoclassical models have been measured in several tokamaks around the world during the last decade, calling into question the reduction of turbulence by sheared radial electric fields in H-mode tokamak pedestals. However, these pioneering theories neglect the impurity diamagnetic drift, or fail to…

### Electrodynamic friction of a charged particle passing a conducting plate. (arXiv:1911.06369v1 [physics.class-ph])

The classical electromagnetic friction of a charged particle moving with prescribed constant velocity parallel to a planar imperfectly conducting surface is reinvestigated. As a concrete example, the Drude model is used to describe the conductor. The transverse electric and transverse magnetic contributions have very different character both in the low velocity (nonrelativistic) and high velocity…

### MmWave Radar Point Cloud Segmentation using GMM in Multimodal Traffic Monitoring. (arXiv:1911.06364v1 [eess.SP])

In the multimodal traffic monitoring, we gather traffic statistics for distinct transportation modes, such as pedestrians, cars and bicycles, in order to analyze and improve people’s daily mobility in terms of safety and convenience. On account of its robustness to bad light and adverse weather conditions, and inherent speed measurement ability, the radar sensor is…

### Automotive Radar Interference Mitigation Using Adaptive Noise Canceller. (arXiv:1911.06372v1 [eess.SP])

Interference among frequency modulated continues wave automotive radars can either increase the noise floor, which occurs in the most cases, or generate a ghost target in rare situations. To address the increment of noise floor due to interference, we proposed a low calculation cost method using adaptive noise canceller to increase the signal-to-interference ratio. In…

### Solving Inverse Problems by Joint Posterior Maximization with a VAE Prior. (arXiv:1911.06379v1 [stat.ML])

In this paper we address the problem of solving ill-posed inverse problems in imaging where the prior is a neural generative model. Specifically we consider the decoupled case where the prior is trained once and can be reused for many different log-concave degradation models without retraining. Whereas previous MAP-based approaches to this problem lead to…

### Unlabeled Sensing With Local Permutations. (arXiv:1911.06382v1 [eess.SP])

Unlabeled sensing is a linear inverse problem where the measurements are scrambled with an unknown permutation resulting in a loss of correspondence to the measurement matrix. In this paper, we consider a special case of the unlabeled sensing problem where we restrict the class of permutations to be local and allow for multiple views. This…

### Seq-U-Net: A One-Dimensional Causal U-Net for Efficient Sequence Modelling. (arXiv:1911.06393v1 [cs.LG])

Convolutional neural networks (CNNs) with dilated filters such as the Wavenet or the Temporal Convolutional Network (TCN) have shown good results in a variety of sequence modelling tasks. However, efficiently modelling long-term dependencies in these sequences is still challenging. Although the receptive field of these models grows exponentially with the number of layers, computing the…

### Contrast Phase Classification with a Generative Adversarial Network. (arXiv:1911.06395v1 [eess.IV])

Dynamic contrast enhanced computed tomography (CT) is an imaging technique that provides critical information on the relationship of vascular structure and dynamics in the context of underlying anatomy. A key challenge for image processing with contrast enhanced CT is that phase discrepancies are latent in different tissues due to contrast protocols, vascular dynamics, and metabolism…

### Modelling EHR timeseries by restricting feature interaction. (arXiv:1911.06410v1 [cs.LG])

Time series data are prevalent in electronic health records, mostly in the form of physiological parameters such as vital signs and lab tests. The patterns of these values may be significant indicators of patients’ clinical states and there might be patterns that are unknown to clinicians but are highly predictive of some outcomes. Many of…

### Synthetic Event Time Series Health Data Generation. (arXiv:1911.06411v1 [cs.LG])

Synthetic medical data which preserves privacy while maintaining utility can be used as an alternative to real medical data, which has privacy costs and resource constraints associated with it. At present, most models focus on generating cross-sectional health data which is not necessarily representative of real data. In reality, medical data is longitudinal in nature,…

### Thirteen Simple Steps for Creating An R Package with an External C++ Library. (arXiv:1911.06416v1 [stat.CO])

We desribe how we extend R with an external C++ code library by using the Rcpp package. Our working example uses the recent machine learning library and application ‘Corels’ providing optimal yet easily interpretable rule lists <arXiv:1704.01701> which we bring to R in the form of the ‘RcppCorels’ package. We discuss each step in the…

### Assessing the uncertainty in statistical evidence with the possibility of model misspecification using a non-parametric bootstrap. (arXiv:1911.06421v1 [stat.ME])

Empirical evidence, e.g. observed likelihood ratio, is an estimator of the difference of the divergences between two competing models (or, model sets) and the true generating mechanism. It is unclear how to use such empirical evidence in scientific practice. Scientists usually want to know “how often would I get this level of evidence”. The answer…

### CASTER: Predicting Drug Interactions with Chemical Substructure Representation. (arXiv:1911.06446v1 [cs.LG])

Adverse drug-drug interactions (DDIs) remain a leading cause of morbidity and mortality. Identifying potential DDIs during the drug design process is critical for patients and society. Although several computational models have been proposed for DDI prediction, there are still limitations: (1) specialized design of drug representation for DDI predictions is lacking; (2) predictions are based…

### Measurement Error Correction in Particle Tracking Microrheology. (arXiv:1911.06451v1 [stat.AP])

In diverse biological applications, particle tracking of passive microscopic species has become the experimental measurement of choice — when either the materials are of limited volume, or so soft as to deform uncontrollably when manipulated by traditional instruments. In a wide range of particle tracking experiments, a ubiquitous finding is that the mean squared displacement…

### Mechanical equivalence of Rander-Finsler spacetimes via Jacobi metric and Eisenhart lift. (arXiv:1911.06321v1 [gr-qc])

In this article, I first review preliminaries of point particle mechanics, introduce the nature and role of the constraint of a mechanical system, and the nature of Killing vectors as explicit symmetry of a geodesic. Then, starting from a general Randers-Finsler spacetime, I describe how the Jacobi-Maupertuis and Eisenhart lift formulations produce a different Rander-…

### Auto-encoding a Knowledge Graph Using a Deep Belief Network: A Random Fields Perspective. (arXiv:1911.06322v1 [cs.NE])

We started with a knowledge graph of connected entities and descriptive properties of those entities, from which, a hierarchical representation of the knowledge graph is derived. Using a graphical, energy-based neural network, we are able to show that the structure of the hierarchy can be internally captured by the neural network, which allows for efficient…

### On the Behaviour of Coalgebras with Side Effects and Algebras with Effectful Iteration. (arXiv:1911.06346v1 [cs.LO])

For every finitary monad $T$ on sets and every endofunctor $F$ on the category of $T$-algebras we introduce the concept of an ffg-Elgot algebra for $F$, that is, an algebra admitting coherent solutions for finite systems of recursive equations with effects represented by the monad $T$. The goal is to study the existence and construction…

### Extremes of Vector-Valued Gaussian Processes. (arXiv:1911.06350v1 [math.PR])

The seminal papers of Pickands [1,2] paved the way for a systematic study of high exceedance probabilities of both stationary and non-stationary Gaussian processes. Yet, in the vector-valued setting, due to the lack of key tools including Slepian’s Lemma, Borell-TIS and Piterbarg inequalities there has not been any methodological development in the literature for the…

### Shape optimisation of stirring rods in mixing binary fluids. (arXiv:1911.06351v1 [physics.flu-dyn])

Mixing is an omnipresent process in a wide-range of industrial applications, which supports scientific efforts to devise techniques for optimising mixing processes under time and energy constraints. In this endeavor, we present a computational framework based on nonlinear direct-adjoint looping for the enhancement of mixing efficiency in a binary fluid system. The governing equations consist…

### Quantum Electron Transport in Degenerate Donor-Acceptor Systems. (arXiv:1911.06370v1 [quant-ph])

We develop a mathematically rigorous theory for the quantum transfer processes in degenerate donor-acceptor dimers in contact with a thermal environment. We calculate explicitly the transfer rates and the acceptor population efficiency. The latter depends critically on the initial donor state. We show that quantum coherence in the initial state enhances the transfer process. If…

### Auto-encoding a Knowledge Graph Using a Deep Belief Network: A Random Fields Perspective. (arXiv:1911.06322v1 [cs.NE])

We started with a knowledge graph of connected entities and descriptive properties of those entities, from which, a hierarchical representation of the knowledge graph is derived. Using a graphical, energy-based neural network, we are able to show that the structure of the hierarchy can be internally captured by the neural network, which allows for efficient…

### On the Behaviour of Coalgebras with Side Effects and Algebras with Effectful Iteration. (arXiv:1911.06346v1 [cs.LO])

For every finitary monad $T$ on sets and every endofunctor $F$ on the category of $T$-algebras we introduce the concept of an ffg-Elgot algebra for $F$, that is, an algebra admitting coherent solutions for finite systems of recursive equations with effects represented by the monad $T$. The goal is to study the existence and construction…

### In Search of the Fastest Concurrent Union-Find Algorithm. (arXiv:1911.06347v1 [cs.DS])

Union-Find (or Disjoint-Set Union) is one of the fundamental problems in computer science; it has been well-studied from both theoretical and practical perspectives in the sequential case. Recently, there has been mounting interest in analyzing this problem in the concurrent scenario, and several asymptotically-efficient algorithms have been proposed. Yet, to date, there is very little…

### Quasinormal-mode modeling and design in nonlinear nano-optics. (arXiv:1911.06373v1 [physics.optics])

Based on quasinormal-mode theory, we propose a novel approach enabling a deep analytical insight into the multi-parameter design and optimization of nonlinear photonic structures at subwavelength scale. A key distinction of our method from previous formulations relying on multipolar Mie-scattering expansions is that it directly exploits the natural resonant modes of the nanostructures, which provide…

### Spatially Heterogeneous Dynamics of Cells in a Growing Tumor Spheroid: Comparison Between Theory and Experiments. (arXiv:1911.06383v1 [physics.bio-ph])

Collective cell movement, characterized by multiple cells that are in contact for substantial periods of time and undergo correlated motion, plays a central role in cancer and embryogenesis. Recent imaging experiments have provided time-dependent traces of individual cells, thus providing an unprecedented picture of tumor spheroid growth. By using simulations of a minimal cell model,…

### Maxwell’s definition of electric polarization as displacement. (arXiv:1911.06387v1 [physics.class-ph])

After reaffirming that the macroscopic dipolar electromagnetic equations, which today are commonly referred to as Maxwell’s equations, are found in Maxwell’s Treatise, we explain from his Treatise that Maxwell defined his displacement vector D as the electric polarization and did not introduce in his Treatise or papers the concept of electric polarization P or the…

### Near source fluorescence spectroscopy for miniaturized thermal atomic beams. (arXiv:1911.06388v1 [physics.atom-ph])

Miniature atomic beams can provide new functionalities for atom based sensing instruments such as atomic clocks and interferometers. We recently demonstrated a planar silicon device for generating well-collimated thermal atomic beams [Nat Commun 10, 1831 (2019)]. Here, we present a near-source fluorescence spectroscopy (NSFS) technique that can fully characterize such miniature beams even when measured…

### Depletion Imaging of Rydberg atoms in cold atomic gases. (arXiv:1911.06397v1 [physics.atom-ph])

We present a depletion imaging technique to map out the spatial and temporal dependency of the density distribution of an ultracold gas of Rydberg atoms. Locally resolved absorption depletion, observed through differential ground state absorption imaging of a $^{87}\text{Rb}$ cloud in presence and absence of pre-excited Rydberg atoms, reveals their projected two-dimensional distribution. By employing…

### Axisymmetric flows on the torus geometry. (arXiv:1911.06401v1 [physics.flu-dyn])

We present a series of analytically solvable axisymmetric flows on the torus geometry. For the single-component flows, we describe the propagation of sound waves for perfect fluids, as well as the viscous damping of shear and longitudinal waves for isothermal and thermal fluids. Unlike the case of planar geometry, the non-uniform curvature on a torus…

### Mechanical squeezing via fast continuous measurement. (arXiv:1911.06412v1 [quant-ph])

We revisit quantum state preparation of an oscillator by continuous linear position measurement. Quite general analytical expressions are derived for the conditioned state of the oscillator. Remarkably, we predict that quantum squeezing is possible outside of both the backaction dominated and quantum coherent oscillation regimes, relaxing experimental requirements even compared to ground-state cooling. This provides…

### On the Homogeneity of TiN Kinetic Inductance Detectors Produced through Atomic Layer Deposition. (arXiv:1911.06419v1 [physics.ins-det])

The non-homogeneity in the critical temperature $T_{c}$ of an Microwave Kinetic Inductance Detector (MKID) could be caused by non-uniformity in the deposition process of the thin superconducting film. This produces low percent yield and frequency collision in the readout of the MKIDs. Here, we show the homogeneity that offers Atomic Layer Deposition (ALD). We report…

### Sensitivity of the COHERENT Experiment to Accelerator-Produced Dark Matter. (arXiv:1911.06422v1 [hep-ex])

The COHERENT experiment is well poised to test sub-GeV dark matter models using low-energy recoil detectors sensitive to coherent elastic neutrino-nucleus scattering (CEvNS) in the $\pi$-DAR neutrino beam produced by the Spallation Neutron Source. We show how a planned 750-kg liquid argon scintillation detector would place leading limits on scalar light dark matter models, over…

### Interaction of Biased Electrodes and Plasmas: Sheaths, Double Layers and Fireballs. (arXiv:1911.06424v1 [physics.plasm-ph])

Biased electrodes are common components of plasma sources and diagnostics. The plasma-electrode interaction is mediated by an intervening sheath structure that influences properties of the electrons and ions contacting the electrode surface, as well as how the electrode influences properties of the bulk plasma. A rich variety of sheath structures have been observed, including ion…

### Resist or perish: fate of a microbial population subjected to a periodic presence of antimicrobial. (arXiv:1911.06425v1 [q-bio.PE])

The evolution of antimicrobial resistance can be strongly affected by variations of antimicrobial concentration. Here, we study the impact of periodic alternations of absence and presence of antimicrobial on resistance evolution in a microbial population, using a stochastic model that includes variations of both population composition and size, and fully incorporates stochastic population extinctions. We…

### Origin of the instability in dynamic fracture. (arXiv:1911.06426v1 [cond-mat.soft])

Unstable growth of cracks (rough crack surface, crack branching) in dynamic fracture have long been observed in various materials. But up to now, no universally agreed-on explanation for why these instabilities happen. Here, we demonstrate that: 1) due to the non-uniform stress distribution in cracked body and the high stress region expands as crack velocity…

### The Boundedness of the Ornstein-Uhlenbeck semigroup on variable Lebesgue spaces with respect to the Gaussian measure. (arXiv:1911.06375v1 [math.CA])

The main result of this work is the proof of the boundedness of the Ornstein-Uhlenbeck semigroup $ \{T_t \}_{t\geq 0} $ in $ {\mathbb R}^d $ on Gaussian variable Lebesgue spaces under a condition of regularity on $p(\cdot)$ following previous papers by E. Dalmaso R. Scotto and S. P\’erez. As a consequence of this result,…

### Solving Inverse Problems by Joint Posterior Maximization with a VAE Prior. (arXiv:1911.06379v1 [stat.ML])

In this paper we address the problem of solving ill-posed inverse problems in imaging where the prior is a neural generative model. Specifically we consider the decoupled case where the prior is trained once and can be reused for many different log-concave degradation models without retraining. Whereas previous MAP-based approaches to this problem lead to…

### Existence of solutions to the Lichnerowicz equation: a new proof. (arXiv:1911.06381v1 [gr-qc])

We provide a complete study of existence and uniqueness of solutions to the Lichnerowicz equation in general relativity with arbitrary mean curvature.

### Entanglement-assisted Quantum Codes from Cyclic Codes. (arXiv:1911.06384v1 [cs.IT])

Entanglement-assisted quantum (QUENTA) codes are a subclass of quantum error-correcting codes which use entanglement as a resource. These codes can provide error correction capability higher than the codes derived from the traditional stabilizer formalism. In this paper, it is shown a general method to construct QUENTA codes from cyclic codes. Afterwards, the method is applied…

### Estimation of dynamic networks for high-dimensional nonstationary time series. (arXiv:1911.06385v1 [math.ST])

This paper is concerned with the estimation of time-varying networks for high-dimensional nonstationary time series. Two types of dynamic behaviors are considered: structural breaks (i.e., abrupt change points) and smooth changes. To simultaneously handle these two types of time-varying features, a two-step approach is proposed: multiple change point locations are first identified based on comparing…

### On the Time-Based Conclusion Stability of Software Defect Prediction Models. (arXiv:1911.06348v1 [cs.SE])

Researchers in empirical software engineering often make claims based on observable data such as defect reports. Unfortunately, in many cases, these claims are generalized beyond the data sets that have been evaluated. Will the researcher’s conclusions hold a year from now for the same software projects? Perhaps not. Recent studies show that in the area…

### Transcendental simplicial volumes. (arXiv:1911.06386v1 [math.GT])

We show that there exist closed manifolds with arbitrarily small transcendental simplicial volumes. Moreover, we exhibit an explicit uncountable family of (transcendental) real numbers that are not realised as the simplicial volume of a closed manifold.

### Question-Conditioned Counterfactual Image Generation for VQA. (arXiv:1911.06352v1 [cs.CV])

While Visual Question Answering (VQA) models continue to push the state-of-the-art forward, they largely remain black-boxes – failing to provide insight into how or why an answer is generated. In this ongoing work, we propose addressing this shortcoming by learning to generate counterfactual images for a VQA model – i.e. given a question-image pair, we…

### Capturing the Production of the Innovative Ideas: An Online Social Network Experiment and “Idea Geography” Visualization. (arXiv:1911.06353v1 [cs.SI])

Collective design and innovation are crucial in organizations. To investigate how the collective design and innovation processes would be affected by the diversity of knowledge and background of collective individual members, we conducted three collaborative design task experiments which involved nearly 300 participants who worked together anonymously in a social network structure using a custom-made…

### Language Inclusion for Finite Prime Event Structures. (arXiv:1911.06355v1 [cs.FL])

We study the problem of language inclusion between finite, labeled prime event structures. Prime event structures are a formalism to compactly represent concurrent behavior of discrete systems. A labeled prime event structure induces a language of sequences of labels produced by the represented system. We study the problem of deciding inclusion and membership for languages…

### Predicting Drug-Drug Interactions from Molecular Structure Images. (arXiv:1911.06356v1 [cs.LG])

Predicting and discovering drug-drug interactions (DDIs) is an important problem and has been studied extensively both from medical and machine learning point of view. Almost all of the machine learning approaches have focused on text data or textual representation of the structural data of drugs. We present the first work that uses drug structure images…

### Give me (un)certainty — An exploration of parameters that affect segmentation uncertainty. (arXiv:1911.06357v1 [eess.IV])

Segmentation tasks in medical imaging are inherently ambiguous: the boundary of a target structure is oftentimes unclear due to image quality and biological factors. As such, predicted segmentations from deep learning algorithms are inherently ambiguous. Additionally, “ground truth” segmentations performed by human annotators are in fact weak labels that further increase the uncertainty of outputs…

### Adjusted Parallel Transport for Higher Gauge Theories. (arXiv:1911.06390v1 [hep-th])

Many physical theories, including notably string theory, require non-abelian higher gauge fields defining higher holonomy. Previous approaches to such higher connections on categorified principal bundles require these to be fake flat. This condition, however, renders them locally gauge equivalent to connections on abelian gerbes. For particular higher gauge groups, for example 2-group models of the…

### Construction of a blow-up solution for a perturbed nonlinear heat equation with a gradient term. (arXiv:1911.06392v1 [math.AP])

We consider in this paper a perturbation of the standard semilinear heat equation by a term involving the space derivative and a non-local term. We prove the existence of a blow-up solution, and give its blow-up profile. Our method relies on the two-step method: we first linearize the equation (in similarity variables) around the expected…

### Strongly uncontrollable network topologies. (arXiv:1911.06398v1 [math.OC])

In this paper, we present a class of network topologies under which the Laplacian consensus dynamics exhibits undesirable controllability properties under a broadcast control signal. Specifically, the networks we characterize are uncontrollable for any subset of the nodes chosen as control inputs and that emit a common control signal. We provide a sufficient condition for…

### Equivariant dendroidal sets and simplicial operads. (arXiv:1911.06399v1 [math.AT])

We establish a Quillen equivalence between the homotopy theories of equivariant Segal operads and equivariant simplicial operads with norm maps. Together with previous work, we further conclude that the homotopy coherent nerve is a right-Quillen equivalence from the model category of equivariant simplicial operads with norm maps to the model category structure for equivariant-$\infty$-operads in…

### New Bounds on $k$-Planar Crossing Numbers. (arXiv:1911.06403v1 [cs.CG])

The crossing number $cr(G)$ of a graph $G$ is the minimum number of crossings over all possible drawings of $G$ in the plane. Analogously, the $k$-planar crossing number of $G$, denoted by $cr_{k}(G)$, is the minimum number of crossings over all possible drawings of the edges of $G$ in $k$ disjoint planes. We present new…

### Directed sets and topological spaces definable in o-minimal structures. (arXiv:1911.06409v1 [math.LO])

We study directed sets definable in o-minimal structures, showing that in expansions of ordered fields these admit cofinal definable curves, as well as a suitable analogue in expansions of ordered groups, and furthermore that no analogue holds in full generality. We use the theory of tame pairs to extend the results in the field case…

### Reversible Hardware for Acoustic Communications. (arXiv:1911.06438v1 [cs.ET])

Reversible computation has been recognised as a potential solution to the technological bottleneck in the future of computing machinery. Rolf Landauer determined the lower limit for power dissipation in computation and noted that dissipation happens when information is lost, i.e., when a bit is erased. This meant that reversible computation, conserving information conserves energy as…

### Structural Controllability of Networked Relative Coupling Systems under Fixed and Switching Topologies. (arXiv:1911.06450v1 [eess.SY])

This paper studies controllability of networked systems in which subsystems are of general high-order linear dynamics and coupled through relative state variables, from a structure perspective. The purpose is to search conditions for subsystem dynamics and subsystem interaction topologies, under which there exists a set of weights for the interaction links such that the associated…

### Estimating adaptive cruise control model parameters from on-board radar units. (arXiv:1911.06454v1 [stat.AP])

Two new methods are presented for estimating car-following model parameters using data collected from the Adaptive Cruise Control (ACC) enabled vehicles. The vehicle is assumed to follow a constant time headway relative velocity model in which the parameters are unknown and to be determined. The first technique is a batch method that uses a least-squares…

### Fourier Spectrum Discrepancies in Deep Network Generated Images. (arXiv:1911.06465v1 [eess.IV])

Advancements in deep generative models such as generative adversarial networks and variational autoencoders have resulted in the ability to generate realistic images that are visually indistinguishable from real images. In this paper, we present an analysis of the high-frequency Fourier modes of real and deep network generated images and the effects of resolution and image…

### Interpreting chest X-rays via CNNs that exploit disease dependencies and uncertainty labels. (arXiv:1911.06475v1 [eess.IV])

Chest radiography is one of the most common types of diagnostic radiology exams, which is critical for screening and diagnosis of many different thoracic diseases. Specialized algorithms have been developed to detect several specific pathologies such as lung nodule or lung cancer. However, accurately detecting the presence of multiple diseases from chest X-rays (CXRs) is…

### Deep Long Audio Inpainting. (arXiv:1911.06476v1 [cs.SD])

Long (> 200 ms) audio inpainting, to recover a long missing part in an audio segment, could be widely applied to audio editing tasks and transmission loss recovery. It is a very challenging problem due to the high dimensional, complex and non-correlated audio features. While deep learning models have made tremendous progress in image and…

### Hardness of Learning DNFs using Halfspaces. (arXiv:1911.06358v1 [cs.CC])

The problem of learning $t$-term DNF formulas (for $t = O(1)$) has been studied extensively in the PAC model since its introduction by Valiant (STOC 1984). A $t$-term DNF can be efficiently learnt using a $t$-term DNF only if $t = 1$ i.e., when it is an AND, while even weakly learning a $2$-term DNF…

### Twitter Watch: Leveraging Social Media to Monitor and Predict Collective-Efficacy of Neighborhoods. (arXiv:1911.06359v1 [cs.SI])

Sociologists associate the spatial variation of crime within an urban setting, with the concept of collective efficacy. The collective efficacy of a neighborhood is defined as social cohesion among neighbors combined with their willingness to intervene on behalf of the common good. Sociologists measure collective efficacy by conducting survey studies designed to measure individuals’ perception…

### Arguing Ecosystem Values with Paraconsistent Logics. (arXiv:1911.06367v1 [cs.LO])

The valuation of ecosystem services prompts dialogical settings where non-trivially inconsistent arguments are often invoked. Here, I propose an approach to the valuation of ecosystem services circumscribed to a logic-based argumentation framework that caters for valid inconsistencies. This framework accounts for preference formation processes underpinned by a paraconsistent model of logical entailment. The value of…

### Entanglement-assisted Quantum Codes from Cyclic Codes. (arXiv:1911.06384v1 [cs.IT])

Entanglement-assisted quantum (QUENTA) codes are a subclass of quantum error-correcting codes which use entanglement as a resource. These codes can provide error correction capability higher than the codes derived from the traditional stabilizer formalism. In this paper, it is shown a general method to construct QUENTA codes from cyclic codes. Afterwards, the method is applied…

### Reduction Monads and Their Signatures. (arXiv:1911.06391v1 [cs.PL])

In this work, we study ‘reduction monads’, which are essentially the same as monads relative to the free functor from sets into multigraphs. Reduction monads account for two aspects of the lambda calculus: on the one hand, in the monadic viewpoint, the lambda calculus is an object equipped with a well-behaved substitution; on the other…

### Estimating adaptive cruise control model parameters from on-board radar units. (arXiv:1911.06454v1 [stat.AP])

Two new methods are presented for estimating car-following model parameters using data collected from the Adaptive Cruise Control (ACC) enabled vehicles. The vehicle is assumed to follow a constant time headway relative velocity model in which the parameters are unknown and to be determined. The first technique is a batch method that uses a least-squares…

### Graph Transformer Networks. (arXiv:1911.06455v1 [cs.LG])

Graph neural networks (GNNs) have been widely used in representation learning on graphs and achieved state-of-the-art performance in tasks such as node classification and link prediction. However, most existing GNNs are designed to learn node representations on the fixed and homogeneous graphs. The limitations especially become problematic when learning representations on a misspecified graph or…

### Optimal Mini-Batch Size Selection for Fast Gradient Descent. (arXiv:1911.06459v1 [cs.LG])

This paper presents a methodology for selecting the mini-batch size that minimizes Stochastic Gradient Descent (SGD) learning time for single and multiple learner problems. By decoupling algorithmic analysis issues from hardware and software implementation details, we reveal a robust empirical inverse law between mini-batch size and the average number of SGD updates required to converge…

### Fourier Spectrum Discrepancies in Deep Network Generated Images. (arXiv:1911.06465v1 [eess.IV])

Advancements in deep generative models such as generative adversarial networks and variational autoencoders have resulted in the ability to generate realistic images that are visually indistinguishable from real images. In this paper, we present an analysis of the high-frequency Fourier modes of real and deep network generated images and the effects of resolution and image…

### $\ell_{\infty}$ Vector Contraction for Rademacher Complexity. (arXiv:1911.06468v1 [cs.LG])

We show that the Rademacher complexity of any $\mathbb{R}^{K}$-valued function class composed with an $\ell_{\infty}$-Lipschitz function is bounded by the maximum Rademacher complexity of the restriction of the function class along each coordinate, times a factor of $\tilde{O}(\sqrt{K})$.

### ASCAI: Adaptive Sampling for acquiring Compact AI. (arXiv:1911.06471v1 [cs.LG])

This paper introduces ASCAI, a novel adaptive sampling methodology that can learn how to effectively compress Deep Neural Networks (DNNs) for accelerated inference on resource-constrained platforms. Modern DNN compression techniques comprise various hyperparameters that require per-layer customization to ensure high accuracy. Choosing such hyperparameters is cumbersome as the pertinent search space grows exponentially with the…

### Spatially Heterogeneous Dynamics of Cells in a Growing Tumor Spheroid: Comparison Between Theory and Experiments. (arXiv:1911.06383v1 [physics.bio-ph])

Collective cell movement, characterized by multiple cells that are in contact for substantial periods of time and undergo correlated motion, plays a central role in cancer and embryogenesis. Recent imaging experiments have provided time-dependent traces of individual cells, thus providing an unprecedented picture of tumor spheroid growth. By using simulations of a minimal cell model,…

### Resist or perish: fate of a microbial population subjected to a periodic presence of antimicrobial. (arXiv:1911.06425v1 [q-bio.PE])

The evolution of antimicrobial resistance can be strongly affected by variations of antimicrobial concentration. Here, we study the impact of periodic alternations of absence and presence of antimicrobial on resistance evolution in a microbial population, using a stochastic model that includes variations of both population composition and size, and fully incorporates stochastic population extinctions. We…

### Radically Compositional Cognitive Concepts. (arXiv:1911.06602v1 [q-bio.NC])

Despite ample evidence that our concepts, our cognitive architecture, and mathematics itself are all deeply compositional, few models take advantage of this structure. We therefore propose a radically compositional approach to computational neuroscience, drawing on the methods of applied category theory. We describe how these tools grant us a means to overcome complexity and improve…

### All-optical frequency resolved optical gating for isolated attosecond pulse reconstruction. (arXiv:1911.06427v1 [physics.optics])

We demonstrate an all-optical approach for precise characterization of attosecond extreme ultraviolet pulses. Isolated attosecond pulse is produced from high order harmonics using intense driving pulse with proper gating technique. When a weak field is synchronized with the driver, it perturbs the harmonics generation process via altering the accumulated phase of the electron trajectories. The…

### Design and Performance of Hafnium Optical and Near-IR Kinetic Inductance Detectors. (arXiv:1911.06434v1 [astro-ph.IM])

We report on the design and performance of Microwave Kinetic Inductance Detectors (MKIDs) sensitive to single photons in the optical to near-infrared range using hafnium as the sensor material. Our test device had a superconducting transition temperature of 395 mK and a room temperature normal state resistivity of 97 $\mu \Omega$ cm with an RRR…

### Reversible Hardware for Acoustic Communications. (arXiv:1911.06438v1 [cs.ET])

Reversible computation has been recognised as a potential solution to the technological bottleneck in the future of computing machinery. Rolf Landauer determined the lower limit for power dissipation in computation and noted that dissipation happens when information is lost, i.e., when a bit is erased. This meant that reversible computation, conserving information conserves energy as…

### Resilience of Urban Transport Network-of-Networks under Intense Flood Hazards Exacerbated by Targeted Attacks. (arXiv:1911.06440v1 [physics.soc-ph])

Natural hazards including floods can trigger catastrophic failures in interdependent urban transport network-of-networks (NoNs). Population growth has enhanced transportation demand while urbanization and climate change have intensified urban floods. However, despite the clear need to develop actionable insights for improving the resilience of critical urban lifelines, the theory and methods remain underdeveloped. Furthermore, as infrastructure…

### The Apollo ATCA Platform. (arXiv:1911.06452v1 [physics.ins-det])

We have developed a novel and generic open-source platform – Apollo – which simplifies the design of custom Advanced Telecommunications Computing Architecture (ATCA) blades by factoring the design into generic infrastructure and application-specific parts. The Apollo “Service Module” provides the required ATCA Intelligent Platform Management Controller, power entry and conditioning, a powerful system-on-module (SoM) computer,…

### Demonstration of a quantized acoustic octupole topological insulator. (arXiv:1911.06469v1 [cond-mat.mtrl-sci])

Recently extended from the modern theory of electric polarization, quantized multipole topological insulators (QMTIs) describe higher-order multipole moments, lying in nested Wilson loops, which are inherently quantized by lattice symmetries. Overlooked in the past, QMTIs reveal new types of gapped boundaries, which themselves represent lower-dimensional topological phases and host topologically protected zero-dimensional (0D) corner states.…

### A Survey of Algorithms for Distributed Charging Control of Electric Vehicles in Smart Grid. (arXiv:1911.06500v1 [eess.SY])

Electric vehicles (EVs) are an eco-friendly alternative to vehicles with internal combustion engines. Despite their environmental benefits, the massive electricity demand imposed by the anticipated proliferation of EVs could jeopardize the secure and economic operation of the power grid. Hence, proper strategies for charging coordination will be indispensable to the future power grid. Coordinated EV…

### A Neural Network Assisted Greedy Algorithm For Sparse Electromagnetic Imaging. (arXiv:1911.06514v1 [eess.SP])

Greedy pursuit algorithms (GPAs), are well appreciated candidates for accurate and efficient reconstruction of sparse signal and image processing applications. Even though many electromagnetic (EM) imaging applications are naturally sparse, GPAs have rarely been explored for this purpose. This is because, for accurate reconstruction, GPAs require (i) the exact number of non-zeros, ‘k’, in the…

### On the Frobenius Complexity of Stanley-Reisner Rings. (arXiv:1911.06417v1 [math.AC])

The Frobenius complexity of a local ring $R$ measures asymptotically the abundance of Frobenius operators of order $e$ on the injective hull of the residue field of $R$. It is known that, for Stanley-Reisner rings, the Frobenius complexity is either $-\infty$ or $0$. This invariant is determined by the complexity sequence $\{c_ e\}_e $ of…

### Improving PHY-Security of UAV-Enabled Transmission with Wireless Energy Harvesting: Robust Trajectory Design and Power Allocation. (arXiv:1911.06516v1 [cs.IT])

In this paper, we consider an unmanned aerial vehicle (UAV) assisted communications system, including two cooperative UAVs, a wireless-powered ground destination node leveraging simultaneous wireless information and power transfer (SWIPT) technique, and a terrestrial passive eavesdropper. One UAV delivers confidential information to destination and the other sends jamming signals to against eavesdropping and assist destination…

### A Novel Content Caching and Delivery Scheme for Millimeter Wave Device-to-Device Communications. (arXiv:1911.06517v1 [eess.SP])

A novel content caching strategy is proposed for a cache enabled device-to-device (D2D) network where the user devices are allowed to communicate using millimeter wave (mmWave) D2D links (> 6 GHz) as well as conventional sub 6 GHz cellular links. The proposed content placement strategy maximizes the successful content delivery probability of a line of…

### Sharp Riesz-Fej\’er inequality for harmonic Hardy spaces. (arXiv:1911.06429v1 [math.FA])

We prove sharp version of Riesz-Fej\’er inequality for functions in harmonic Hardy space $h^p(\mathbb{D})$ on the unit disk $\mathbb{D}$, for $p>1,$ thus extending the result from \cite{KPK} and resolving the posed conjecture.

### Safe Coverage of Compact Domains For Second Order Dynamical Systems. (arXiv:1911.06519v1 [eess.SY])

Autonomous systems operating in close proximity with each other to cover a specified area has many potential applications, but to achieve effective coordination, two key challenges need to be addressed: coordination and safety. For coordination, we propose a locally asymptotically stable distributed coverage controller for compact domains in the plane and homogeneous vehicles modeled with…

### Localization for Random Walks in Random Environment in Dimension two and Higher. (arXiv:1911.06430v1 [math.PR])

In this paper, we introduce the notion of \textit{localization at the boundary} for random walks in i.i.d. and uniformly elliptic random environment, in dimensions two and higher. Informally, this means that the walk spends a non-trivial amount of time at some point $x\in \mathbb{Z}^{d}$ with $||x||_{1}=n$ at time $n$, for $n$ large enough. In dimensions…

### An Energy Efficient D2D Model with Guaranteed Quality of Service for Cloud Radio Access Networks. (arXiv:1911.06528v1 [eess.SP])

This paper proposes a spectrum selection scheme and a transmit power minimization scheme for a device-to-device (D2D) network cross-laid with a cloud radio access network (CRAN). The D2D communications are allowed as an overlay to the CRAN as well as in the unlicensed industrial, scientific and medical radio (ISM) band. A link distance based scheme…

### Singularities of fourfold blowups. (arXiv:1911.06435v1 [math.AG])

We answer a question raised by Birkar, who asked for conditions under which a weighted blow-up of affine 4-space would not have terminal singularities.

### Atypical exit events near a repelling equilibrium. (arXiv:1911.06437v1 [math.PR])

We consider exit problems for small white noise perturbations of a dynamical system generated by a vector field, and a domain containing a critical point with all positive eigenvalues of linearization. We prove that, in the vanishing noise limit, the probability of exit through a generic set on the boundary is asymptotically polynomial in the…

### Bounds to the Normal Approximation for Linear Recursions with Two Effects. (arXiv:1911.06444v1 [math.PR])

Let $X_0$ be a non-constant random variable with finite variance. Given an integer $k\ge2$, define a sequence $\{X_n\}_{n=1}^\infty$ of approximately linear recursions with small perturbations $\{\Delta_n\}_{n=0}^\infty$ by $$X_{n+1} = \sum_{i=1}^k a_{n,i} X_{n,i} + \Delta_n \quad \text{for all } n\ge0$$ where $X_{n,1},\dots,X_{n,k}$ are independent copies of the $X_n$ and $a_{n,1},\dots,a_{n,k}$ are real numbers. In 2004, Goldstein…

### Seq-U-Net: A One-Dimensional Causal U-Net for Efficient Sequence Modelling. (arXiv:1911.06393v1 [cs.LG])

Convolutional neural networks (CNNs) with dilated filters such as the Wavenet or the Temporal Convolutional Network (TCN) have shown good results in a variety of sequence modelling tasks. However, efficiently modelling long-term dependencies in these sequences is still challenging. Although the receptive field of these models grows exponentially with the number of layers, computing the…

### The Eighth Dialog System Technology Challenge. (arXiv:1911.06394v1 [cs.CL])

This paper introduces the Eighth Dialog System Technology Challenge. In line with recent challenges, the eighth edition focuses on applying end-to-end dialog technologies in a pragmatic way for multi-domain task-completion, noetic response selection, audio visual scene-aware dialog, and schema-guided dialog state tracking tasks. This paper describes the task definition, provided datasets, and evaluation set-up for…

### Contrast Phase Classification with a Generative Adversarial Network. (arXiv:1911.06395v1 [eess.IV])

Dynamic contrast enhanced computed tomography (CT) is an imaging technique that provides critical information on the relationship of vascular structure and dynamics in the context of underlying anatomy. A key challenge for image processing with contrast enhanced CT is that phase discrepancies are latent in different tissues due to contrast protocols, vascular dynamics, and metabolism…

### Does Face Recognition Accuracy Get Better With Age? Deep Face Matchers Say No. (arXiv:1911.06396v1 [cs.CV])

Previous studies generally agree that face recognition accuracy is higher for older persons than for younger persons. But most previous studies were before the wave of deep learning matchers, and most considered accuracy only in terms of the verification rate for genuine pairs. This paper investigates accuracy for age groups 16-29, 30-49 and 50-70, using…

### Transformer-CNN: Fast and Reliable tool for QSAR. (arXiv:1911.06603v1 [q-bio.QM])

We present SMILES-embeddings derived from internal encoder state of a Transformer[1] model trained to canonize SMILES as a Seq2Seq problem. Using CharNN[2] architecture upon the embeddings results in a higher quality QSAR/QSPR models on diverse benchmark datasets including regression and classification tasks. The proposed Transformer-CNN method uses SMILES augmentation for training and inference, and thus…

### Regeneration comes for free with biological development in a generative Boolean model. (arXiv:1911.06659v1 [q-bio.MN])

To transform a single-celled zygote into an adult multicellular organism, development employs three basic processes — asymmetric cell division, signaling and gene regulation. These three processes can be combined in a multitude of ways, thus generating the huge diversity of plant and animal forms we see today. The wealth of possible developmental schemes created by…

### New Approaches in Synthetic Biology: Abiotic Organelles and Artificial Cells Powered and Controlled by Light. (arXiv:1911.06684v1 [q-bio.SC])

One of the major goals of nanobionics and bottom-up synthetic biology is the development of artificial cell organelles for the creation of cell-like structures operating similar to biological systems with a minimalistic set of building blocks. In the present contribution, versatile strategies to develop artificial reaction centers for novel photoautotrophic processes and to provide fully…

### Deep radiomic features from MRI scans predict survival outcome of recurrent glioblastoma. (arXiv:1911.06687v1 [cs.CV])

This paper proposes to use deep radiomic features (DRFs) from a convolutional neural network (CNN) to model fine-grained texture signatures in the radiomic analysis of recurrent glioblastoma (rGBM). We use DRFs to predict survival of rGBM patients with preoperative T1-weighted post-contrast MR images (n=100). DRFs are extracted from regions of interest labelled by a radiation…

### A Tale of Two Desolvation Potentials: An Investigation of Protein Behavior Under High Hydrostatic Pressure. (arXiv:1911.06692v1 [q-bio.BM])

Hydrostatic pressure is a common perturbation to probe the conformations of proteins. There are two common forms of pressure dependent potentials of mean force (PMFs) derived from hydrophobic molecules available for the coarse grained molecular simulations of protein folding and unfolding under hydrostatic pressure. Although both PMF includes a desolvation barrier separating the well of…

### A RBA model for the chemostat modeling. (arXiv:1911.06696v1 [q-bio.CB])

The purpose of this paper is to show that it is possible to replace Monod’s type model of a chemostat by a constraint based model of bacteria at the genome scale. This new model is an extension of the RBA model of bacteria developed in a batch mode to the chemostat. This new model, and…

### Explicit-Blurred Memory Network for Analyzing Patient Electronic Health Records. (arXiv:1911.06472v1 [cs.LG])

In recent years, we have witnessed an increased interest in temporal modeling of patient records from large scale Electronic Health Records (EHR). While simpler RNN models have been used for such problems, memory networks, which in other domains were found to generalize well, are underutilized. Traditional memory networks involve diffused and non-linear operations where influence…

### Sequential Recommendation with Relation-Aware Kernelized Self-Attention. (arXiv:1911.06478v1 [cs.LG])

Recent studies identified that sequential Recommendation is improved by the attention mechanism. By following this development, we propose Relation-Aware Kernelized Self-Attention (RKSA) adopting a self-attention mechanism of the Transformer with augmentation of a probabilistic model. The original self-attention of Transformer is a deterministic measure without relation-awareness. Therefore, we introduce a latent space to the self-attention,…

### On Model Robustness Against Adversarial Examples. (arXiv:1911.06479v1 [cs.LG])

We study the model robustness against adversarial examples, referred to as small perturbed input data that may however fool many state-of-the-art deep learning models. Unlike previous research, we establish a novel theory addressing the robustness issue from the perspective of stability of the loss function in the small neighborhood of natural examples. We propose to…

### OpenLORIS-Object: A Dataset and Benchmark towards Lifelong Object Recognition. (arXiv:1911.06487v1 [cs.CV])

The recent breakthroughs in computer vision have benefited from the availability of large representative datasets (e.g. ImageNet and COCO) for training. Yet, robotic vision poses unique challenges for applying visual algorithms developed from these standard computer vision datasets due to their implicit assumption over non-varying distributions for a fixed set of tasks. Fully retraining models…

### Single View Distortion Correction using Semantic Guidance. (arXiv:1911.06505v1 [cs.CV])

Most distortion correction methods focus on simple forms of distortion, such as radial or linear distortions. These works undistort images either based on measurements in the presence of a calibration grid, or use multiple views to find point correspondences and predict distortion parameters. When possible distortions are more complex, e.g. in the case of a…

### Likelihood Assignment for Out-of-Distribution Inputs in Deep Generative Models is Sensitive to Prior Distribution Choice. (arXiv:1911.06515v1 [stat.ML])

Recent work has shown that deep generative models assign higher likelihood to out-of-distribution inputs than to training data. We show that a factor underlying this phenomenon is a mismatch between the nature of the prior distribution and that of the data distribution, a problem found in widely used deep generative models such as VAEs and…

### Toward Scalable Many-Body Calculations for Nuclear Open Quantum Systems using the Gamow Shell Model. (arXiv:1911.06494v1 [physics.comp-ph])

Drip-line nuclei have very different properties from those of the valley of stability, as they are weakly bound and resonant. Therefore, the models devised for stable nuclei can no longer be applied therein. Hence, a new theoretical tool, the Gamow Shell Model (GSM), has been developed to study the many-body states occurring at the limits…

### Characterization of ionization injection in gas mixtures irradiated by sub-petawatt class laser pulses. (arXiv:1911.06512v1 [physics.plasm-ph])

Effects of ionization injection in low and high Z gas mixtures for the laser wake field acceleration of electrons are analyzed with the use of balance equations and particle-in-cell simulations via test probe particle trajectories in realistic plasma fields and direct simulations of charge loading during the ionization process. It is shown that electrons appearing…

### Random walks on hypergraphs. (arXiv:1911.06523v1 [physics.soc-ph])

In the last twenty years network science has proven its strength in modelling many real-world interacting systems as generic agents, the nodes, connected by pairwise edges. Yet, in many relevant cases, interactions are not pairwise but involve larger sets of nodes, at a time. These systems are thus better described in the framework of hypergraphs,…

### Comparison of counterstreaming suprathermal electron signatures of ICMEs with and without magnetic cloud: are all ICMEs flux ropes?. (arXiv:1911.06526v1 [physics.space-ph])

Magnetic clouds (MCs), as large-scale interplanetary magnetic flux ropes, are usually still connected to the sun at both ends near 1 AU. Many researchers believe that all non-MC interplanetary coronal mass ejections (ICMEs) also have magnetic flux rope structures, which are inconspicuous because the observing spacecraft crosses the flanks of the rope structures. If so,…

### Dynamic Evolution of a Transient Supersonic Trailing Jet Induced by a Strong Incident Shock Wave. (arXiv:1911.06530v1 [physics.flu-dyn])

The dynamic evolution of a highly underexpanded transient supersonic jet at the exit of a pulse detonation engine is investigated via high-resolution time-resolved schlieren and numerical simulations. Experimental evidence is provided for the presence of a second triple shock configuration along with a shocklet between the reflected shock and the slipstream, which has no analogue…

### Detecting regime transitions of the nocturnal and Polar boundary layer. (arXiv:1911.06533v1 [physics.ao-ph])

Many natural systems undergo critical transitions, i.e. sudden shifts from one dynamical regime to another. In the climate system, the atmospheric boundary layer can experience sudden transitions between fully turbulent states and quiescent, quasi-laminar states. Such rapid transitions are observed in Polar regions or at night when the atmospheric boundary layer is stably stratified, and…

### Hypergraph Contextuality. (arXiv:1911.06448v1 [quant-ph])

Quantum contextuality is a source of quantum computational power and a theoretical delimiter between classical and quantum structures. It has been substantiated by numerous experiments and prompted generation of state independent contextual sets, that is, sets of quantum observables capable of revealing quantum contextuality for any quantum state of a given dimension. There are two…

### Quadratic addition rules for three $q$-integers. (arXiv:1911.06449v1 [math.CO])

The $q$-integer is the polynomial $[n]_q = 1 + q + q^2 + \dots + q^{n-1}$. For every sequences of polynomials $\mathcal S = \{s_m(q)\}_{m=1}^\infty$, $\mathcal T = \{t_m(q)\}_{m=1}^\infty$, $\mathcal U = \{u_m(q)\}_{m=1}^\infty$ and $\mathcal V = \{v_m(q)\}_{m=1}^\infty$, define an addition rule for three $q$-integers by $$\oplus_{\mathcal S,\mathcal T,\mathcal U,\mathcal V} ([m]_q, [n]_q, [k]_q) =…

### Holder regularity and exponential decay of correlations for a class of piecewise partially hyperbolic maps. (arXiv:1911.06457v1 [math.DS])

We consider a class of systems which contains a set of piecewise partially hyperbolic dynamics semi-conjugated to non-uniformly expanding maps. The aimed transformation, preserves a foliation which is almost every uniformly contracted with possible discontinuity sets, which are parallel to the contracting direction. We prove that the associated transfer operator, acting on suitable anisotropic normed…

### Distributed Nash equilibrium seeking for aggregative games via a small-gain approach. (arXiv:1911.06458v1 [math.OC])

Distributed Nash equilibrium seeking of aggregative games is investigated and a continuous-time algorithm is proposed. The algorithm is designed by virtue of projected gradient play dynamics and distributed average tracking dynamics, and is applicable to games with constrained strategy sets and weight-balanced communication graphs. We analyze the complex interaction of these dynamics with the help…

### Flexible Functional Split and Power Control for Energy Harvesting Cloud Radio Access Networks. (arXiv:1911.06463v1 [cs.NI])

Functional split is a promising technique to flexibly balance the processing cost at remote ends and the fronthaul rate in cloud radio access networks (C-RAN). By harvesting renewable energy, remote radio units (RRUs) can save grid power and be flexibly deployed. However, the randomness of energy arrival poses a major design challenge. To maximize the…

### Controllability of the Voter Model: an information theoretic approach. (arXiv:1911.06540v1 [eess.SY])

We address the link between the controllability or observability of a stochastic complex system and concepts of information theory. We show that the most influential degrees of freedom can be detected without acting on the system, by measuring the time-delayed multi-information. Numerical and analytical results support this claim, which is developed in the case of…

### Longitudinal analysis of fetal MRI in patients with prenatal spina bifida repair. (arXiv:1911.06542v1 [eess.IV])

Open spina bifida (SB) is one of the most common congenital defects and can lead to impaired brain development. Emerging fetal surgery methods have shown considerable success in the treatment of patients with this severe anomaly. Afterwards, alterations in the brain development of these fetuses have been observed. Currently no longitudinal studies exist to show…

### Computing higher symplectic capacities I. (arXiv:1911.06466v1 [math.SG])

We present recursive formulas which compute the recently defined “higher symplectic capacities” for all convex toric domains. In the special case of four-dimensional ellipsoids, we apply homological perturbation theory to the associated filtered L-infinity algebras and prove that the resulting structure coefficients count punctured pseudoholomorphic curves in cobordisms between ellipsoids. As sample applications, we produce…

### A meshfree formulation for large deformation analysis of flexoelectric structures accounting for the surface effects. (arXiv:1911.06553v1 [physics.comp-ph])

In this work, we present a compactly supported radial basis function (CSRBF) based meshfree method to analyse geometrically nonlinear flexoelectric nanostructures considering surface effects. Flexoelectricity is the polarization of dielectric materials due to the gradient of strain, which is different from piezoelectricity in which polarization is dependent linearly on strain. The surface effects gain prominence…

### Safe Interactive Model-Based Learning. (arXiv:1911.06556v1 [eess.SY])

Control applications present hard operational constraints. A violation of this can result in unsafe behavior. This paper introduces Safe Interactive Model Based Learning (SiMBL), a framework to refine an existing controller and a system model while operating on the real environment. SiMBL is composed of the following trainable components: a Lyapunov function, which determines a…

### Tracking the circulation routes of fresh coins in Bitcoin: A way of identifying coin miners with transaction network structural properties. (arXiv:1911.06400v1 [q-fin.GN])

Bitcoin draws the highest degree of attention among cryptocurrencies, while coin mining is one of the most important fashion of profiting in the Bitcoin ecosystem. This paper constructs fresh coin circulation networks by tracking the fresh coin transfer routes with transaction referencing in Bitcoin blockchain. This paper proposes a heuristic algorithm to identifying coin miners…

### New Bounds on $k$-Planar Crossing Numbers. (arXiv:1911.06403v1 [cs.CG])

The crossing number $cr(G)$ of a graph $G$ is the minimum number of crossings over all possible drawings of $G$ in the plane. Analogously, the $k$-planar crossing number of $G$, denoted by $cr_{k}(G)$, is the minimum number of crossings over all possible drawings of the edges of $G$ in $k$ disjoint planes. We present new…

### Mining News Events from Comparable News Corpora: A Multi-Attribute Proximity Network Modeling Approach. (arXiv:1911.06407v1 [cs.LG])

We present ProxiModel, a novel event mining framework for extracting high-quality structured event knowledge from large, redundant, and noisy news data sources. The proposed model differentiates itself from other approaches by modeling both the event correlation within each individual document as well as across the corpus. To facilitate this, we introduce the concept of a…

### Design Requirements of Generic Hand Exoskeletons and Survey of Hand Exoskeletons for Rehabilitation, Assistive or Haptic Use. (arXiv:1911.06408v1 [cs.RO])

Most current hand exoskeletons have been designed specifically for rehabilitation, assistive or haptic applications to simplify the design requirements. Clinical studies on post-stroke rehabilitation have shown that adapting assistive or haptic applications into physical therapy sessions significantly improves the motor learning and treatment process. The recent technology can lead to the creation of generic hand…

### Modelling EHR timeseries by restricting feature interaction. (arXiv:1911.06410v1 [cs.LG])

Time series data are prevalent in electronic health records, mostly in the form of physiological parameters such as vital signs and lab tests. The patterns of these values may be significant indicators of patients’ clinical states and there might be patterns that are unknown to clinicians but are highly predictive of some outcomes. Many of…

### Synthetic Event Time Series Health Data Generation. (arXiv:1911.06411v1 [cs.LG])

Synthetic medical data which preserves privacy while maintaining utility can be used as an alternative to real medical data, which has privacy costs and resource constraints associated with it. At present, most models focus on generating cross-sectional health data which is not necessarily representative of real data. In reality, medical data is longitudinal in nature,…

### Tracking the circulation routes of fresh coins in Bitcoin: A way of identifying coin miners with transaction network structural properties. (arXiv:1911.06400v1 [q-fin.GN])

Bitcoin draws the highest degree of attention among cryptocurrencies, while coin mining is one of the most important fashion of profiting in the Bitcoin ecosystem. This paper constructs fresh coin circulation networks by tracking the fresh coin transfer routes with transaction referencing in Bitcoin blockchain. This paper proposes a heuristic algorithm to identifying coin miners…

### Optimal intervention strategies of staged progression HIV infections through an age-structured model with probabilities of ART drop out. (arXiv:1911.06703v1 [math.AP])

In this paper, we construct a model to describe the transmission of HIV in a homogeneous host population. By considering the specific mechanism of HIV, we derive a model structured in three successive stages: (i) primary infection, (ii) long phase of latency without symptoms and (iii) AIDS. Each HIV stage is stratified by the duration…

### Asymptotics of Quasi-Stationary Distributions of Small Noise Stochastic Dynamical Systems in Unbounded Domains. (arXiv:1911.06707v1 [math.PR])

We consider a collection of Markov chains that model the evolution of multitype biological populations. The state space of the chains is the positive orthant, and the boundary of the orthant is absorbing representing the extinction states of different population types. We are interested in the long-term behavior of the Markov chain away from extinction,…

### A crossover code for high-dimensional composition. (arXiv:1911.06775v1 [q-bio.NC])

We present a novel way to encode compositional information in high-dimensional (HD) vectors. Inspired by chromosomal crossover, random HD vectors are recursively interwoven, with a fraction of one vector’s components masked out and replaced by those from another using a context-dependent mask. Unlike many HD computing schemes, “crossover” codes highly overlap with their base elements’…

### Mechanism of reconstitution/activation of the soluble PQQ-dependent glucose dehydrogenase from Acinetobacter calcoaceticus: a comprehensive study. (arXiv:1911.06795v1 [q-bio.BM])

The ability to switch on the activity of an enzyme through its spontaneous reconstitution has proven to be a valuable tool in fundamental studies of enzyme structure/reactivity relationships or in the design of artificial signal transduction systems in bioelectronics, synthetic biology, or bioanalytical applications. In particular, those based on the spontaneous reconstitution/activation of the apo-PQQ-dependent…

### Spatial eco-evolutionary feedbacks mediate coexistence in prey-predator systems. (arXiv:1902.03016v2 [q-bio.PE] UPDATED)

Eco-evolutionary frameworks can explain certain features of communities in which ecological and evolutionary processes occur over comparable timescales. Here, we investigate whether an evolutionary dynamics may interact with the spatial structure of a prey-predator community in which both species show limited mobility and predator perceptual ranges are subject to natural selection. In these conditions, our…

### Improvement of the Izhikevich model based on the rat basolateral amygdala and hippocampus neurons, and recognition of their possible firing patterns. (arXiv:1910.11380v2 [cs.NE] UPDATED)

Introduction: Identifying the potential firing patterns following by different brain regions under normal and abnormal conditions increases our understanding of what is happening in the level of neural interactions in the brain. On the other hand, it is important to be capable of modeling the potential neural activities, in order to build precise artificial neural…

### Optimal Sequential Tests for Detection of Changes under Finite measure space for Finite Sequences of Networks. (arXiv:1911.06545v1 [math.ST])

This paper considers the change-point problem for finite sequences of networks. To avoid the difficulty of computing the normalization coefficient, such as in Exponential random graphical models (ERGMs) and Markov networks, we construct a finite measure space with measure ratio statistics. A new performance measure of detection delay is proposed to detect the changes in…

### Multi-Label Learning with Deep Forest. (arXiv:1911.06557v1 [cs.LG])

In multi-label learning, each instance is associated with multiple labels and the crucial task is how to leverage label correlations in building models. Deep neural network methods usually jointly embed the feature and label information into a latent space to exploit label correlations. However, the success of these methods highly depends on the precise choice…

### Akaike’s Bayesian information criterion (ABIC) or not ABIC for geophysical inversion. (arXiv:1911.06564v1 [stat.ME])

Akaike’s Bayesian information criterion (ABIC) has been widely used in geophysical inversion and beyond. However, little has been done to investigate its statistical aspects. We present an alternative derivation of the marginal distribution of measurements, whose maximization directly leads to the invention of ABIC by Akaike. We show that ABIC is to statistically estimate the…

### GET: Global envelopes in R. (arXiv:1911.06583v1 [stat.ME])

This work describes the R package GET that implements global envelopes, which can be employed for central regions of functional or multivariate data, for graphical Monte Carlo and permutation tests where the test statistic is multivariate or functional, and for global confidence and prediction bands. Intrinsic graphical interpretation property is introduced for global envelopes, and…

### Deep learning methods in speaker recognition: a review. (arXiv:1911.06615v1 [eess.AS])

This paper summarizes the applied deep learning practices in the field of speaker recognition, both verification and identification. Speaker recognition has been a widely used field topic of speech technology. Many research works have been carried out and little progress has been achieved in the past 5-6 years. However, as deep learning techniques do advance…

### Detecting cutaneous basal cell carcinomas in ultra-high resolution and weakly labelled histopathological images. (arXiv:1911.06616v1 [eess.IV])

Diagnosing basal cell carcinomas (BCC), one of the most common cutaneous malignancies in humans, is a task regularly performed by pathologists and dermato-pathologists. Improving histological diagnosis by providing diagnosis suggestions, i.e. computer-assisted diagnoses is actively researched to improve safety, quality and efficiency. Increasingly, machine learning methods are applied due to their superior performance. However, typical…

### Feedback Linearization based on Gaussian Processes with event-triggered Online Learning. (arXiv:1911.06565v1 [eess.SY])

Combining control engineering with nonparametric modeling techniques from machine learning allows to control systems without analytic description using data-