Graphical Models

Scaling MPE Inference for Constrained Continuous Markov Random Fields with Consensus Optimization NeurIPS 2012 Semiparametric Pseudo-Likelihood Estimation in Markov Random Fields AISTATS 2012 Simultaneously Leveraging Output and Task Structures for Multiple-Output Regression NeurIPS 2012 Slice Normalized Dynamic Markov Logic Networks NeurIPS 2012 Smooth-projected Neighborhood Pursuit for High-dimensional Nonparanormal Graph Estimation NeurIPS 2012 Sparsistency of the Edge Lasso over Graphs AISTATS 2012 Spectral Clustering of Graphs with General Degrees in the Extended Planted Partition Model COLT 2012 Spectral Learning of General Weighted Automata via Constrained Matrix Completion NeurIPS 2012 Structured Learning of Gaussian Graphical Models NeurIPS 2012 Structure estimation for discrete graphical models: Generalized covariance matrices and their inverses NeurIPS 2012 The Bethe Partition Function of Log-supermodular Graphical Models NeurIPS 2012 The huge Package for High-dimensional Undirected Graph Estimation in R JMLR 2012 Topic-Partitioned Multinetwork Embeddings NeurIPS 2012 Topology Constraints in Graphical Models NeurIPS 2012 Transelliptical Graphical Models NeurIPS 2012 Variable Selection for Gaussian Graphical Models AISTATS 2012 Variational Inference for Crowdsourcing NeurIPS 2012 θ-MRF: Capturing Spatial and Semantic Structure in the Parameters for Scene Understanding NeurIPS 2011 An Application of Tree-Structured Expectation Propagation for Channel Decoding NeurIPS 2011 Bagged Structure Learning of Bayesian Network AISTATS 2011 Collective Graphical Models NeurIPS 2011 Data Skeletonization via Reeb Graphs NeurIPS 2011 Discussion of “Learning Scale Free Networks by Reweighted ℓ_1 regularization” AISTATS 2011 Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials NeurIPS 2011 Empirical models of spiking in neural populations NeurIPS 2011