Graphical Models

Training Factor Graphs with Reinforcement Learning for Efficient MAP Inference NeurIPS 2009 Which graphical models are difficult to learn? NeurIPS 2009 Adaptive Body Scheme Models for Robust Robotic Manipulation RSS 2008 Bayesian Network Score Approximation using a Metagraph Kernel NeurIPS 2008 Bounds on marginal probability distributions NeurIPS 2008 Clusters and Coarse Partitions in LP Relaxations NeurIPS 2008 Continuously-adaptive discretization for message-passing algorithms NeurIPS 2008 Counting Solution Clusters in Graph Coloring Problems Using Belief Propagation NeurIPS 2008 Dependence of Orientation Tuning on Recurrent Excitation and Inhibition in a Network Model of V1 NeurIPS 2008 Efficient Exact Inference in Planar Ising Models NeurIPS 2008 Fast Prediction on a Tree NeurIPS 2008 Finding Latent Causes in Causal Networks: an Efficient Approach Based on Markov Blankets NeurIPS 2008 Gates NeurIPS 2008 Hierarchical Semi-Markov Conditional Random Fields for Recursive Sequential Data NeurIPS 2008 Influence of graph construction on graph-based clustering measures NeurIPS 2008 Integrating Locally Learned Causal Structures with Overlapping Variables NeurIPS 2008 Kernel Measures of Independence for non-iid Data NeurIPS 2008 Learning Bounded Treewidth Bayesian Networks NeurIPS 2008 MAS: a multiplicative approximation scheme for probabilistic inference NeurIPS 2008 Model Selection in Gaussian Graphical Models: High-Dimensional Consistency of \boldmath$\ell_1$-regularized MLE NeurIPS 2008 Multiscale Random Fields with Application to Contour Grouping NeurIPS 2008 Partially Observed Maximum Entropy Discrimination Markov Networks NeurIPS 2008 Predicting the Geometry of Metal Binding Sites from Protein Sequence NeurIPS 2008 Robust Near-Isometric Matching via Structured Learning of Graphical Models NeurIPS 2008 Sparse Signal Recovery Using Markov Random Fields NeurIPS 2008