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BMCBI
2008
166views more  BMCBI 2008»
15 years 3 months ago
Learning transcriptional regulatory networks from high throughput gene expression data using continuous three-way mutual informa
Background: Probability based statistical learning methods such as mutual information and Bayesian networks have emerged as a major category of tools for reverse engineering mecha...
Weijun Luo, Kurt D. Hankenson, Peter J. Woolf
143
Voted
RECOMB
2004
Springer
16 years 3 months ago
Learning Regulatory Network Models that Represent Regulator States and Roles
Abstract. We present an approach to inferring probabilistic models of generegulatory networks that is intended to provide a more mechanistic representation of transcriptional regul...
Keith Noto, Mark Craven
116
Voted
WSDM
2010
ACM
254views Data Mining» more  WSDM 2010»
16 years 25 days ago
Learning Influence Probabilities In Social Networks
Recently, there has been tremendous interest in the phenomenon of influence propagation in social networks. The studies in this area assume they have as input to their problems a ...
Amit Goyal 0002, Francesco Bonchi, Laks V. S. Laks...
161
Voted
IEEECIT
2006
IEEE
15 years 9 months ago
Adaptive Routing for Sensor Networks using Reinforcement Learning
Efficient and robust routing is central to wireless sensor networks (WSN) that feature energy-constrained nodes, unreliable links, and frequent topology change. While most existi...
Ping Wang, Ting Wang
142
Voted
ICDAR
2009
IEEE
15 years 1 months ago
Learning Bayesian Networks by Evolution for Classifier Combination
Combining classifier methods have shown their effectiveness in a number of applications. Nonetheless, using simultaneously multiple classifiers may result in some cases in a reduc...
Claudio De Stefano, Francesco Fontanella, Alessand...