graphical model

Bayesian Model Scoring in Markov Random Fields NeurIPS 2006 Efficient Structure Learning of Markov Networks using L_1-Regularization NeurIPS 2006 High-Dimensional Graphical Model Selection Using ℓ_1-Regularized Logistic Regression NeurIPS 2006 Inferring Network Structure from Co-Occurrences NeurIPS 2006 Learning Factor Graphs in Polynomial Time and Sample Complexity JMLR 2006 Learning Nonparametric Models for Probabilistic Imitation NeurIPS 2006 Learning with Hypergraphs: Clustering, Classification, and Embedding NeurIPS 2006 Linear Programming Relaxations and Belief Propagation -- An Empirical Study JMLR 2006 Multi-dynamic Bayesian Networks NeurIPS 2006 Training Conditional Random Fields for Maximum Labelwise Accuracy NeurIPS 2006 Learning Hidden Variable Networks: The Information Bottleneck Approach JMLR 2005 Loopy Belief Propagation: Convergence and Effects of Message Errors JMLR 2005 Exact Bayesian Structure Discovery in Bayesian Networks JMLR 2004 Reinforcement Learning with Factored States and Actions JMLR 2004 Learning Probabilistic Models of Link Structure JMLR 2002 The Representational Power of Discrete Bayesian Networks JMLR 2002 Dependency Networks for Inference, Collaborative Filtering, and Data Visualization JMLR 2000