Graph Theory

Faithfulness in Chain Graphs: The Gaussian Case AISTATS 2011 Faster Algorithms for Max-Product Message-Passing JMLR 2011 Forest Density Estimation JMLR 2011 High-dimensional Covariance Estimation Based On Gaussian Graphical Models JMLR 2011 High-Dimensional Graphical Model Selection: Tractable Graph Families and Necessary Conditions NeurIPS 2011 Learning High-Dimensional Markov Forest Distributions: Analysis of Error Rates JMLR 2011 Learning Higher-Order Graph Structure with Features by Structure Penalty NeurIPS 2011 Learning Latent Tree Graphical Models JMLR 2011 Learning Scale Free Networks by Reweighted ℓ_1 regularization AISTATS 2011 Maximal Cliques that Satisfy Hard Constraints with Application to Deformable Object Model Learning NeurIPS 2011 Mixed Cumulative Distribution Networks AISTATS 2011 On Time Varying Undirected Graphs AISTATS 2011 Parallel Algorithm for Learning Optimal Bayesian Network Structure JMLR 2011 Phase transition in the family of p-resistances NeurIPS 2011 Reconstructing Patterns of Information Diffusion from Incomplete Observations NeurIPS 2011 Regularized Laplacian Estimation and Fast Eigenvector Approximation NeurIPS 2011 Revisiting MAP Estimation, Message Passing and Perfect Graphs AISTATS 2011 See the Tree Through the Lines: The Shazoo Algorithm NeurIPS 2011 Spectral Methods for Learning Multivariate Latent Tree Structure NeurIPS 2011 Structure Learning for Optimization NeurIPS 2011 Uniqueness of Belief Propagation on Signed Graphs NeurIPS 2011 Approximate Inference on Planar Graphs using Loop Calculus and Belief Propagation JMLR 2010 Characterization, Stability and Convergence of Hierarchical Clustering Methods JMLR 2010 Detecting Weak but Hierarchically-Structured Patterns in Networks AISTATS 2010 Exact learning curves for Gaussian process regression on large random graphs NeurIPS 2010