Structure Learning

High-Dimensional Graphical Model Selection: Tractable Graph Families and Necessary Conditions NeurIPS 2011 Learning Higher-Order Graph Structure with Features by Structure Penalty NeurIPS 2011 On Learning Discrete Graphical Models using Greedy Methods NeurIPS 2011 Causal discovery in multiple models from different experiments NeurIPS 2010 Efficient Relational Learning with Hidden Variable Detection NeurIPS 2010 Learning Efficient Markov Networks NeurIPS 2010 On the Convexity of Latent Social Network Inference NeurIPS 2010 Nonlinear directed acyclic structure learning with weakly additive noise models NeurIPS 2009 Sparse and Locally Constant Gaussian Graphical Models NeurIPS 2009 Which graphical models are difficult to learn? NeurIPS 2009 Model Selection in Gaussian Graphical Models: High-Dimensional Consistency of \boldmath$\ell_1$-regularized MLE NeurIPS 2008 Non-stationary dynamic Bayesian networks NeurIPS 2008 Structure Learning in Human Sequential Decision-Making NeurIPS 2008 Efficient Principled Learning of Thin Junction Trees NeurIPS 2007 Efficient Structure Learning of Markov Networks using L_1-Regularization NeurIPS 2006 Learning Structural Equation Models for fMRI NeurIPS 2006