Representation

Bayesian structure discovery in Bayesian networks with less space AISTATS 2010 Learning concept graphs from text with stick-breaking priors NeurIPS 2010 Learning Networks of Stochastic Differential Equations NeurIPS 2010 Lifted Inference Seen from the Other Side : The Tractable Features NeurIPS 2010 Link Discovery using Graph Feature Tracking NeurIPS 2010 More data means less inference: A pseudo-max approach to structured learning NeurIPS 2010 On the Convexity of Latent Social Network Inference NeurIPS 2010 Probabilistic Belief Revision with Structural Constraints NeurIPS 2010 Abstraction and Relational learning NeurIPS 2009 Bayesian Sparse Factor Models and DAGs Inference and Comparison NeurIPS 2009 Nonparametric Latent Feature Models for Link Prediction NeurIPS 2009 Incremental Identification of Qualitative Models of Biological Systems using Inductive Logic Programming JMLR 2008 Online Prediction on Large Diameter Graphs NeurIPS 2008 Partially Observed Maximum Entropy Discrimination Markov Networks NeurIPS 2008 Supervised Bipartite Graph Inference NeurIPS 2008 Gaussian Process Models for Link Analysis and Transfer Learning NeurIPS 2007 Hidden Common Cause Relations in Relational Learning NeurIPS 2007 Learning and using relational theories NeurIPS 2007 Bayesian Model Scoring in Markov Random Fields NeurIPS 2006 Inferring Network Structure from Co-Occurrences NeurIPS 2006 Learning annotated hierarchies from relational data NeurIPS 2006 Recursive Attribute Factoring NeurIPS 2006 Stochastic Relational Models for Discriminative Link Prediction NeurIPS 2006 Construction of Conceptual Graph Representation of Texts NAACL 2004 Learning Probabilistic Models of Link Structure JMLR 2002