This paper proposes three novel training methods, two of them based on the back-propagation approach and a third one based on information theory for Multilayer Perceptron (MLP) bin...
Discovering the complex regulatory networks that govern mRNA expression is an important but difficult problem. Many current approaches use only expression data from microarrays to...
Stephen D. Bay, Jeff Shrager, Andrew Pohorille, Pa...
In this work we present algorithms for Minimum Energy Consumption Broadcast Subgraph (MECBS) problem. First, we focus on designing distributed algorithms for MECBS. To our knowled...
we present a cognitively inspired mathematical learning framework called Neural Modeling Fields (NMF). We apply it to learning and recognition of situations composed of objects. NM...
In recent years, there has been a growing interest in applying Bayesian networks and their extensions to reconstruct regulatory networks from gene expression data. Since the gene ...