Biologically inspired architectures for sample-efficient deep reinforcement learning. (arXiv:1911.11285v1 [cs.LG])

Deep reinforcement learning requires a heavy price in terms of sample efficiency and overparameterization in the neural networks used for function approximation. In this work, we use tensor factorization in order to learn more compact representation for reinforcement learning policies. We show empirically that in the low-data regime, it is possible to learn online policies…

Neural Graph Matching Network: Learning Lawler’s Quadratic Assignment Problem with Extension to Hypergraph and Multiple-graph Matching. (arXiv:1911.11308v1 [cs.LG])

Graph matching involves combinatorial optimization based on edge-to-edge affinity matrix, which can be generally formulated as Lawler’s Quadratic Assignment Problem (QAP). This paper presents a QAP network directly learning with the affinity matrix (equivalently the association graph) whereby the matching problem is translated into a vertex classification task. The association graph is learned by an…

Super-Resolution for Practical Automated Plant Disease Diagnosis System. (arXiv:1911.11341v1 [eess.IV])

Automated plant diagnosis using images taken from a distance is often insufficient in resolution and degrades diagnostic accuracy since the important external characteristics of symptoms are lost. In this paper, we first propose an effective pre-processing method for improving the performance of automated plant disease diagnosis systems using super-resolution techniques. We investigate the efficiency of…

An Autonomous Spectrum Management Scheme for Unmanned Aerial Vehicle Networks in Disaster Relief Operations. (arXiv:1911.11343v1 [cs.LG])

This paper studies the problem of spectrum shortage in an unmanned aerial vehicle (UAV) network during critical missions such as wildfire monitoring, search and rescue, and disaster monitoring. Such applications involve a high demand for high-throughput data transmissions such as real-time video-, image-, and voice- streaming where the assigned spectrum to the UAV network may…

Controller Synthesis of Wind Turbine Generator and Energy Storage System with Stochastic Wind Variations under Temporal Logic Specifications. (arXiv:1911.11347v1 [eess.SY])

In this paper, we present a controller synthesis approach for wind turbine generators (WTG) and energy storage systems with metric temporal logic (MTL) specifications, with provable probabilistic guarantees in the stochastic environment of wind power generation. The MTL specifications are requirements for the grid frequency deviations, WTG rotor speed variations and the power flow constraints…

Control of Permanent Magnet Motors with Actuation Bounds using Convex Optimization. (arXiv:1911.11353v1 [eess.SY])

This paper presents a nonlinear control algorithm for speed control of a permanent magnet motor. The idea relies on a feedback linearization technique which also ensures adherence to current and voltage bounds. These bounds arise from practical limitations of the power source. The feedback linearization law is computed using a convex optimization routine to minimize…

Multi-scale Molecular Simulations on Respiratory Complex I. (arXiv:1911.11178v1 [physics.bio-ph])

Complex I (NADH:ubiquinone oxidoreductase) is a redox-driven proton pump that powers synthesis of adenosine triphosphate (ATP) and active transport in most organisms. This gigantic enzyme reduces quinone (Q) to quinol (QH2) in its hydrophilic domain, and transduces the released free energy into pumping of protons across its membrane domain, up to ca. 200 {\AA} away…

Orienting Ordered Scaffolds: Complexity and Algorithms. (arXiv:1911.11190v1 [q-bio.GN])

Despite the recent progress in genome sequencing and assembly, many of the currently available assembled genomes come in a draft form. Such draft genomes consist of a large number of genomic fragments (scaffolds), whose order and/or orientation (i.e., strand) in the genome are unknown. There exist various scaffold assembly methods, which attempt to determine the…

A Binary Particle Swarm Optimization Approach for Gene Expression Biclustering Problem. (arXiv:1911.11223v1 [q-bio.QM])

Microarray techniques are widely used in Gene expression analysis. These techniques are based on discovering submatrices of genes that share similar expression patterns across a set of experimental conditions with coherence constraint. Actually, these submatrices are called biclusters and the extraction process is called biclustering. In this paper we present a novel binary particle swarm…