Graphical Models

Revisiting MAP Estimation, Message Passing and Perfect Graphs AISTATS 2011 Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation NeurIPS 2011 Spectral Clustering on a Budget AISTATS 2011 Spectral Methods for Learning Multivariate Latent Tree Structure NeurIPS 2011 Structure Learning for Optimization NeurIPS 2011 t-divergence Based Approximate Inference NeurIPS 2011 Two is better than one: distinct roles for familiarity and recollection in retrieving palimpsest memories NeurIPS 2011 Uniqueness of Belief Propagation on Signed Graphs NeurIPS 2011 An EM Algorithm on BDDs with Order Encoding for Logic-based Probabilistic Models ACML 2010 Approximate Inference by Compilation to Arithmetic Circuits NeurIPS 2010 Boosted Optimization for Network Classification AISTATS 2010 Brain covariance selection: better individual functional connectivity models using population prior NeurIPS 2010 Collective Inference for Extraction MRFs Coupled with Symmetric Clique Potentials JMLR 2010 Computing Marginal Distributions over Continuous Markov Networks for Statistical Relational Learning NeurIPS 2010 Copula Bayesian Networks NeurIPS 2010 Efficient Relational Learning with Hidden Variable Detection NeurIPS 2010 Evidence-Specific Structures for Rich Tractable CRFs NeurIPS 2010 Exact inference and learning for cumulative distribution functions on loopy graphs NeurIPS 2010 Exploiting Within-Clique Factorizations in Junction-Tree Algorithms AISTATS 2010 Extended Bayesian Information Criteria for Gaussian Graphical Models NeurIPS 2010 Gaussian sampling by local perturbations NeurIPS 2010 Getting lost in space: Large sample analysis of the resistance distance NeurIPS 2010 Graphical Gaussian modelling of multivariate time series with latent variables AISTATS 2010 Graph-Valued Regression NeurIPS 2010 HOP-MAP: Efficient Message Passing with High Order Potentials AISTATS 2010