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Graphical Models

933 directly classified papers

Papers per year

Papers

A Convex Formulation for Learning Scale-Free Networks via Submodular Relaxation NIPS 2012
Link Prediction in Graphs with Autoregressive Features NIPS 2012
Fiedler Random Fields: A Large-Scale Spectral Approach to Statistical Network Modeling NIPS 2012
Scalable Inference of Overlapping Communities NIPS 2012
Learning the Architecture of Sum-Product Networks Using Clustering on Variables NIPS 2012
Spectral Clustering of Graphs with General Degrees in the Extended Planted Partition Model COLT 2012
Topic-Partitioned Multinetwork Embeddings NIPS 2012
Majorization for CRFs and Latent Likelihoods NIPS 2012
Learning Networks of Heterogeneous Influence NIPS 2012
Hidden-Unit Conditional Random Fields AISTATS 2011
On Learning Discrete Graphical Models using Group-Sparse Regularization AISTATS 2011
Fast $b$-matching via Sufficient Selection Belief Propagation AISTATS 2011
Revisiting MAP Estimation, Message Passing and Perfect Graphs AISTATS 2011
Bagged Structure Learning of Bayesian Network AISTATS 2011
Discussion of “Learning Scale Free Networks by Reweighted $\ell_1$ regularization” AISTATS 2011
Learning Scale Free Networks by Reweighted $\ell_1$ regularization AISTATS 2011
Learning equivalence classes of acyclic models with latent and selection variables from multiple datasets with overlapping variables AISTATS 2011
Multicore Gibbs Sampling in Dense, Unstructured Graphs AISTATS 2011
On Learning Discrete Graphical Models using Greedy Methods NIPS 2011
Kernel Belief Propagation AISTATS 2011
Collective Graphical Models NIPS 2011
Probabilistic Joint Image Segmentation and Labeling NIPS 2011
Learning a Distance Metric from a Network NIPS 2011
Kernel Embeddings of Latent Tree Graphical Models NIPS 2011
$\theta$-MRF: Capturing Spatial and Semantic Structure in the Parameters for Scene Understanding NIPS 2011