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RECOMB
2004
Springer
16 years 7 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
CIKM
2009
Springer
16 years 1 months ago
Joint sentiment/topic model for sentiment analysis
Sentiment analysis or opinion mining aims to use automated tools to detect subjective information such as opinions, attitudes, and feelings expressed in text. This paper proposes ...
Chenghua Lin, Yulan He
NIPS
2008
15 years 8 months ago
A mixture model for the evolution of gene expression in non-homogeneous datasets
We address the challenge of assessing conservation of gene expression in complex, non-homogeneous datasets. Recent studies have demonstrated the success of probabilistic models in...
Gerald Quon, Yee Whye Teh, Esther Chan, Timothy R....
UAI
2008
15 years 8 months ago
Church: a language for generative models
Formal languages for probabilistic modeling enable re-use, modularity, and descriptive clarity, and can foster generic inference techniques. We introduce Church, a universal langu...
Noah Goodman, Vikash K. Mansinghka, Daniel M. Roy,...
AAAI
2006
15 years 8 months ago
Bayesian Reputation Modeling in E-Marketplaces Sensitive to Subjectivity, Deception and Change
We present a model for buying agents in e-marketplaces to interpret evaluations of sellers provided by other buying agents, known as advisors. The interpretation of seller evaluat...
Kevin Regan, Pascal Poupart, Robin Cohen