Graphical Models

Learning the Architecture of Sum-Product Networks Using Clustering on Variables NeurIPS 2012 Learning the Dependency Structure of Latent Factors NeurIPS 2012 Learning to Discover Social Circles in Ego Networks NeurIPS 2012 Learning with Partially Absorbing Random Walks NeurIPS 2012 Lightning-speed Structure Learning of Nonlinear Continuous Networks AISTATS 2012 Link Prediction in Graphs with Autoregressive Features NeurIPS 2012 Low rank continuous-space graphical models AISTATS 2012 Majorization for CRFs and Latent Likelihoods NeurIPS 2012 MAP Inference in Chains using Column Generation NeurIPS 2012 Markov Logic Mixtures of Gaussian Processes: Towards Machines Reading Regression Data AISTATS 2012 Max-Margin Structured Output Regression for Spatio-Temporal Action Localization NeurIPS 2012 Memory-efficient inference in dynamic graphical models using multiple cores AISTATS 2012 Minimization of Continuous Bethe Approximations: A Positive Variation NeurIPS 2012 Minimizing Sparse High-Order Energies by Submodular Vertex-Cover NeurIPS 2012 Mixing Properties of Conditional Markov Chains with Unbounded Feature Functions NeurIPS 2012 Newton-Like Methods for Sparse Inverse Covariance Estimation NeurIPS 2012 Nonparanormal Belief Propagation (NPNBP) NeurIPS 2012 On Lifting the Gibbs Sampling Algorithm NeurIPS 2012 Online Sum-Product Computation Over Trees NeurIPS 2012 On Sparse, Spectral and Other Parameterizations of Binary Probabilistic Models AISTATS 2012 On Triangular versus Edge Representations --- Towards Scalable Modeling of Networks NeurIPS 2012 Open Problem: Learning Dynamic Network Models from a Static Snapshot COLT 2012 Quilting Stochastic Kronecker Product Graphs to Generate Multiplicative Attribute Graphs AISTATS 2012 Random function priors for exchangeable arrays with applications to graphs and relational data NeurIPS 2012 Scalable Inference of Overlapping Communities NeurIPS 2012