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TNN
2010
234views Management» more  TNN 2010»
13 years 5 months ago
Novel maximum-margin training algorithms for supervised neural networks
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...
Oswaldo Ludwig, Urbano Nunes
JBI
2002
13 years 10 months ago
Revising regulatory networks: from expression data to linear causal models
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...
CSE
2008
IEEE
14 years 17 days ago
Energy Efficient Broadcast in Distributed Ad Hoc Wireless Networks
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...
Subhas Kumar Ghosh
IJNCR
2010
59views more  IJNCR 2010»
13 years 8 months ago
Cognitively Inspired Neural Network for Recognition of Situations
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...
Roman Ilin, Leonid I. Perlovsky
JMLR
2006
103views more  JMLR 2006»
13 years 10 months ago
MinReg: A Scalable Algorithm for Learning Parsimonious Regulatory Networks in Yeast and Mammals
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 ...
Dana Pe'er, Amos Tanay, Aviv Regev