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LION
2009
Springer
112views Optimization» more  LION 2009»
14 years 4 months ago
A Graph-Based Semi-supervised Algorithm for Protein Function Prediction from Interaction Maps
Abstract. Protein function prediction represents a fundamental challenge in bioinformatics. The increasing availability of proteomics network data has enabled the development of se...
Valerio Freschi
SDM
2012
SIAM
252views Data Mining» more  SDM 2012»
12 years 1 days ago
Learning from Heterogeneous Sources via Gradient Boosting Consensus
Multiple data sources containing different types of features may be available for a given task. For instance, users’ profiles can be used to build recommendation systems. In a...
Xiaoxiao Shi, Jean-François Paiement, David...
UAI
2008
13 years 11 months ago
Hybrid Variational/Gibbs Collapsed Inference in Topic Models
Variational Bayesian inference and (collapsed) Gibbs sampling are the two important classes of inference algorithms for Bayesian networks. Both have their advantages and disadvant...
Max Welling, Yee Whye Teh, Bert Kappen
BMCBI
2006
166views more  BMCBI 2006»
13 years 9 months ago
Extraction of phylogenetic network modules from the metabolic network
Background: In bio-systems, genes, proteins and compounds are related to each other, thus forming complex networks. Although each organism has its individual network, some organis...
Takuji Yamada, Minoru Kanehisa, Susumu Goto
AAAI
1997
13 years 11 months ago
Effective Bayesian Inference for Stochastic Programs
In this paper, we propose a stochastic version of a general purpose functional programming language as a method of modeling stochastic processes. The language contains random choi...
Daphne Koller, David A. McAllester, Avi Pfeffer