An Adaptive Load Balancer For Graph Analytical Applications on GPUs. (arXiv:1911.09135v1 [cs.DC])

Load balancing graph analytics workloads on GPUs is difficult because of the irregular nature of graph applications and the high variability in vertex degrees, particularly in power-law graphs. In this paper, we describe a novel load balancing scheme that aims to address this problem. Our scheme is implemented in the IrGL compiler to allow users…

Motion control for autonomous heterogeneous multi-agent area search in uncertain conditions. (arXiv:1911.09137v1 [math.OC])

Using multiple mobile robots in search missions offers a lot of benefits, but one needs a suitable and competent motion control algorithm which is able to consider sensors characteristics, the uncertainty of target detection and complexity of needed maneuvers in order to make a multi-agent search autonomous. This paper provides a methodology for an autonomous…

ID-aware Quality for Set-based Person Re-identification. (arXiv:1911.09143v1 [cs.CV])

Set-based person re-identification (SReID) is a matching problem that aims to verify whether two sets are of the same identity (ID). Existing SReID models typically generate a feature representation per image and aggregate them to represent the set as a single embedding. However, they can easily be perturbed by noises–perceptually/semantically low quality images–which are inevitable…

DPM: A deep learning PDE augmentation method (with application to large-eddy simulation). (arXiv:1911.09145v1 [cs.LG])

Machine learning for scientific applications faces the challenge of limited data. We propose a framework that leverages a priori known physics to reduce overfitting when training on relatively small datasets. A deep neural network is embedded in a partial differential equation (PDE) that expresses the known physics and learns to describe the corresponding unknown or…

Deadlock Analysis and Resolution in Multi-Robot Systems: The Two Robot Case. (arXiv:1911.09146v1 [cs.RO])

Collision avoidance for multirobot systems is a well studied problem. Recently, control barrier functions (CBFs) have been proposed for synthesizing decentralized controllers that guarantee collision avoidance (safety) and goal stabilization (performance) for multiple robots. However, it has been noted in several works that reactive control synthesis methods (such as CBFs) are prone to deadlock, an…

Concurrency and Privacy with Payment-Channel Networks. (arXiv:1911.09148v1 [cs.CR])

Permissionless blockchains protocols such as Bitcoin are inherently limited in transaction throughput and latency. Current efforts to address this key issue focus on off-chain payment channels that can be combined in a Payment-Channel Network (PCN) to enable an unlimited number of payments without requiring to access the blockchain other than to register the initial and…

Autoregressive Modeling of Forest Dynamics. (arXiv:1911.09182v1 [q-bio.QM])

In this work, we employ autoregressive models developed in financial engineering for modeling of forest dynamics. Autoregressive models have some theoretical advantage over currently employed forest modeling approaches such as Markov chains and individual-based models, as autoregressive models are both analytically tractable and operate with continuous state space. We perform time series statistical analysis of…

Information in Infinite Ensembles of Infinitely-Wide Neural Networks. (arXiv:1911.09189v1 [cs.LG])

In this preliminary work, we study the generalization properties of infinite ensembles of infinitely-wide neural networks. Amazingly, this model family admits tractable calculations for many information-theoretic quantities. We report analytical and empirical investigations in the search for signals that correlate with generalization.

Regression Discontinuity Design under Self-selection. (arXiv:1911.09248v1 [stat.ME])

In Regression Discontinuity (RD) design, self-selection leads to different distributions of covariates on two sides of the policy intervention, which essentially violates the continuity of potential outcome assumption. The standard RD estimand becomes difficult to interpret due to the existence of some indirect effect, i.e. the effect due to self selection. We show that the…