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Graphical Models

985 papers

Papers per year

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Papers

Learning unbelievable probabilities NIPS 2011
$\theta$-MRF: Capturing Spatial and Semantic Structure in the Parameters for Scene Understanding NIPS 2011
Kernel Embeddings of Latent Tree Graphical Models NIPS 2011
Learning a Distance Metric from a Network NIPS 2011
Maximal Cliques that Satisfy Hard Constraints with Application to Deformable Object Model Learning NIPS 2011
Probabilistic Joint Image Segmentation and Labeling NIPS 2011
Collective Graphical Models NIPS 2011
Mapping Kernels Defined Over Countably Infinite Mapping Systems and their Application ACML 2011
Learning equivalence classes of acyclic models with latent and selection variables from multiple datasets with overlapping variables AISTATS 2011
Learning Scale Free Networks by Reweighted $\ell_1$ regularization AISTATS 2011
Discussion of “Learning Scale Free Networks by Reweighted $\ell_1$ regularization” AISTATS 2011
Bagged Structure Learning of Bayesian Network AISTATS 2011
Revisiting MAP Estimation, Message Passing and Perfect Graphs AISTATS 2011
Fast $b$-matching via Sufficient Selection Belief Propagation AISTATS 2011
On Learning Discrete Graphical Models using Group-Sparse Regularization AISTATS 2011
Hidden-Unit Conditional Random Fields AISTATS 2011
Fast Convergent Algorithms for Expectation Propagation Approximate Bayesian Inference AISTATS 2011
Spectral Clustering on a Budget AISTATS 2011
Mixed Cumulative Distribution Networks AISTATS 2011
Kernel Belief Propagation AISTATS 2011
Multicore Gibbs Sampling in Dense, Unstructured Graphs AISTATS 2011
Extended Bayesian Information Criteria for Gaussian Graphical Models NIPS 2010
Getting lost in space: Large sample analysis of the resistance distance NIPS 2010
MAP Estimation for Graphical Models by Likelihood Maximization NIPS 2010
Identifying graph-structured activation patterns in networks NIPS 2010