Graphical Models

Identifying graph-structured activation patterns in networks NeurIPS 2010 Implicit Differentiation by Perturbation NeurIPS 2010 Inference with Multivariate Heavy-Tails in Linear Models NeurIPS 2010 Learning Efficient Markov Networks NeurIPS 2010 Learning Networks of Stochastic Differential Equations NeurIPS 2010 Lifted Inference Seen from the Other Side : The Tractable Features NeurIPS 2010 MAP Estimation for Graphical Models by Likelihood Maximization NeurIPS 2010 MAP estimation in Binary MRFs via Bipartite Multi-cuts NeurIPS 2010 Maximum-likelihood learning of cumulative distribution functions on graphs AISTATS 2010 More data means less inference: A pseudo-max approach to structured learning NeurIPS 2010 Neural conditional random fields AISTATS 2010 Nonparametric Tree Graphical Models AISTATS 2010 On Combining Graph-based Variance Reduction schemes AISTATS 2010 On the Convexity of Latent Social Network Inference NeurIPS 2010 Polynomial-Time Exact Inference in NP-Hard Binary MRFs via Reweighted Perfect Matching AISTATS 2010 Reduced-Rank Hidden Markov Models AISTATS 2010 (RF)^2 -- Random Forest Random Field NeurIPS 2010 Sparse Inverse Covariance Selection via Alternating Linearization Methods NeurIPS 2010 Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models NeurIPS 2010 Structured Determinantal Point Processes NeurIPS 2010 Worst-case bounds on the quality of max-product fixed-points NeurIPS 2010 Accelerating Bayesian Structural Inference for Non-Decomposable Gaussian Graphical Models NeurIPS 2009 A Gaussian Tree Approximation for Integer Least-Squares NeurIPS 2009 An Integer Projected Fixed Point Method for Graph Matching and MAP Inference NeurIPS 2009 An LP View of the M-best MAP problem NeurIPS 2009