Graphical Models

Structured ranking learning using cumulative distribution networks NeurIPS 2008 Supervised Bipartite Graph Inference NeurIPS 2008 The Infinite Factorial Hidden Markov Model NeurIPS 2008 Adaptive Embedded Subgraph Algorithms using Walk-Sum Analysis NeurIPS 2007 Agreement-Based Learning NeurIPS 2007 An Analysis of Convex Relaxations for MAP Estimation NeurIPS 2007 Collective Inference on Markov Models for Modeling Bird Migration NeurIPS 2007 Cooled and Relaxed Survey Propagation for MRFs NeurIPS 2007 Discovering Weakly-Interacting Factors in a Complex Stochastic Process NeurIPS 2007 Dynamic Conditional Random Fields: Factorized Probabilistic Models for Labeling and Segmenting Sequence Data JMLR 2007 Efficient Bayesian Inference for Dynamically Changing Graphs NeurIPS 2007 Efficient Principled Learning of Thin Junction Trees NeurIPS 2007 Estimating High-Dimensional Directed Acyclic Graphs with the PC-Algorithm JMLR 2007 Exponential Family Predictive Representations of State NeurIPS 2007 Fast and Scalable Training of Semi-Supervised CRFs with Application to Activity Recognition NeurIPS 2007 Fixing Max-Product: Convergent Message Passing Algorithms for MAP LP-Relaxations NeurIPS 2007 Gaussian Process Models for Link Analysis and Transfer Learning NeurIPS 2007 GRIFT: A graphical model for inferring visual classification features from human data NeurIPS 2007 Hidden Common Cause Relations in Relational Learning NeurIPS 2007 Learning with Tree-Averaged Densities and Distributions NeurIPS 2007 Linear programming analysis of loopy belief propagation for weighted matching NeurIPS 2007 Local Algorithms for Approximate Inference in Minor-Excluded Graphs NeurIPS 2007 Loop Series and Bethe Variational Bounds in Attractive Graphical Models NeurIPS 2007 Measuring Neural Synchrony by Message Passing NeurIPS 2007 Message Passing for Max-weight Independent Set NeurIPS 2007