Probabilistic Modeling

Online Learning for Latent Dirichlet Allocation NeurIPS 2010 On the Convergence Properties of Contrastive Divergence AISTATS 2010 Parallelizable Sampling of Markov Random Fields AISTATS 2010 Polynomial-Time Exact Inference in NP-Hard Binary MRFs via Reweighted Perfect Matching AISTATS 2010 Predictive Subspace Learning for Multi-view Data: a Large Margin Approach NeurIPS 2010 Probabilistic Belief Revision with Structural Constraints NeurIPS 2010 Probabilistic Deterministic Infinite Automata NeurIPS 2010 Probabilistic Inference and Differential Privacy NeurIPS 2010 Probabilistic latent variable models for distinguishing between cause and effect NeurIPS 2010 Rescaling, thinning or complementing? On goodness-of-fit procedures for point process models and Generalized Linear Models NeurIPS 2010 Self-Paced Learning for Latent Variable Models NeurIPS 2010 Sequential Monte Carlo Samplers for Dirichlet Process Mixtures AISTATS 2010 Shadow Dirichlet for Restricted Probability Modeling NeurIPS 2010 Simple Exponential Family PCA AISTATS 2010 Slice sampling covariance hyperparameters of latent Gaussian models NeurIPS 2010 Solving the Uncapacitated Facility Location Problem Using Message Passing Algorithms AISTATS 2010 Sparse Instrumental Variables (SPIV) for Genome-Wide Studies NeurIPS 2010 Sparse Inverse Covariance Selection via Alternating Linearization Methods NeurIPS 2010 State-Space Inference and Learning with Gaussian Processes AISTATS 2010 Structured Determinantal Point Processes NeurIPS 2010 Supervised Dimension Reduction Using Bayesian Mixture Modeling AISTATS 2010 The Maximal Causes of Natural Scenes are Edge Filters NeurIPS 2010 The Multidimensional Wisdom of Crowds NeurIPS 2010 Tree-Structured Stick Breaking for Hierarchical Data NeurIPS 2010 Unsupervised Aggregation for Classification Problems with Large Numbers of Categories AISTATS 2010