$C$-compact orthogonally additive operators in vector lattices. (arXiv:1911.10255v1 [math.FA])

We consider $C$-compact orthogonally additive operators in vector lattices. In the first part of the article we present some examples of $C$-compact operators defined on a vector lattice and taking value in a Banach space. It is shown that the set of all $C$-compact orthogonally additive operators from a vector lattice $E$ to an order…

Searching for new physics with profile likelihoods: Wilks and beyond. (arXiv:1911.10237v1 [physics.data-an])

Particle physics experiments use likelihood ratio tests extensively to compare hypotheses and to construct confidence intervals. Often, the null distribution of the likelihood ratio test statistic is approximated by a $\chi^2$ distribution, following a theorem due to Wilks. However, many circumstances relevant to modern experiments can cause this theorem to fail. In this paper, we…

Approaching Small Molecule Prioritization as a Cross-Modal Information Retrieval Task through Coordinated Representation Learning. (arXiv:1911.10241v1 [q-bio.QM])

Modeling the relationship between chemical structure and molecular activity is a key task in drug development and precision medicine. In this paper, we utilize a novel deep learning architecture to jointly train coordinated embeddings of chemical structures and transcriptional signatures. We do so by training neural networks in a coordinated manner such that learned chemical…

DeepSynth: Program Synthesis for Automatic Task Segmentation in Deep Reinforcement Learning. (arXiv:1911.10244v1 [cs.LG])

We propose a method for efficient training of deep Reinforcement Learning (RL) agents when the reward is highly sparse and non-Markovian, but at the same time admits a high-level yet unknown sequential structure, as seen in a number of video games. This high-level sequential structure can be expressed as a computer program, which our method…

Non-parametric targeted Bayesian estimation of class proportions in unlabeled data. (arXiv:1911.10246v1 [stat.ME])

We introduce a novel Bayesian estimator for the class proportion in an unlabeled dataset, based on the targeted learning framework. Our procedure requires the specification of a prior (and outputs a posterior) only for the target of inference, instead of the prior (and posterior) on the full-data distribution employed by classical non-parametric Bayesian methods .When…

3rd-order Spectral Representation Method: Part II — Ergodic Multi-variate random processes with fast Fourier transform. (arXiv:1911.10251v1 [math.ST])

The second in a two-part series, this paper extends the 3rd-order Spectral Representation Method for simulation of ergodic multi-variate stochastic processes according to a prescribed cross power spectral density and cross bispectral density. The 2nd and 3rd order ensemble properties of the simulated stochastic vector processes are shown to satisfy the target cross correlation properties…

Shape Detection of Liver From 2D Ultrasound Images. (arXiv:1911.10352v1 [eess.IV])

Applications of ultrasound images have expanded from fetal imaging to abdominal and cardiac diagnosis. Liver-being the largest gland in the body and responsible for metabolic activities requires to be to be diagnosed and therefore subject to utmost injury. Although, ultrasound imaging has developed into three and four dimensions providing higher amount of information; it requires…

Uncertainty Management in Power System Operation Decision Making. (arXiv:1911.10358v1 [eess.SY])

Due to the penetration of renewable energy resources and load deviation, uncertainty handling is one of the main challenges for power system; therefore the need for accurate decision-making in a power system under the penetration of uncertainties is essential. However, decision makers should use suitable methods for uncertainty management. In this chapter, some of the…

Robust cooperative synchronization of homogeneous agents with delays on directed communication graphs. (arXiv:1911.10359v1 [eess.SY])

This study deals with analysis and control of cooperative synchronization for identical agents interacting on a directed graph topology. The agents are considered to have general continuous linear time-invariant dynamics with homogeneous communication and/or control delays. An LMI approach based on a Lyapunov-Krasovskii functional is proposed, together with the synchronizing region concept, which decouples the…