Bayesian & Probabilistic

Markov Mixed Membership Models ICML 2015 Max-Margin Majority Voting for Learning from Crowds NeurIPS 2015 MCMC for Variationally Sparse Gaussian Processes NeurIPS 2015 MCMC Learning COLT 2015 Measuring Sample Quality with Stein's Method NeurIPS 2015 Message Passing for Collective Graphical Models ICML 2015 Metadata Dependent Mondrian Processes ICML 2015 Minimum Weight Perfect Matching via Blossom Belief Propagation NeurIPS 2015 Missing at Random in Graphical Models AISTATS 2015 Multi-Class Multi-Annotator Active Learning With Robust Gaussian Process for Visual Recognition ICCV 2015 Multi-Feature Max-Margin Hierarchical Bayesian Model for Action Recognition CVPR 2015 Nested Sequential Monte Carlo Methods ICML 2015 Neural Adaptive Sequential Monte Carlo NeurIPS 2015 Non-Gaussian Discriminative Factor Models via the Max-Margin Rank-Likelihood ICML 2015 Nonparametric Bayesian Factor Analysis for Dynamic Count Matrices AISTATS 2015 Online Prediction at the Limit of Zero Temperature NeurIPS 2015 Online Rank Elicitation for Plackett-Luce: A Dueling Bandits Approach NeurIPS 2015 On some provably correct cases of variational inference for topic models NeurIPS 2015 On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators NeurIPS 2015 On-the-Job Learning with Bayesian Decision Theory NeurIPS 2015 On the Relationship between Sum-Product Networks and Bayesian Networks ICML 2015 Optimization Monte Carlo: Efficient and Embarrassingly Parallel Likelihood-Free Inference NeurIPS 2015 Parallelizing MCMC with Random Partition Trees NeurIPS 2015 Particle Gibbs for Infinite Hidden Markov Models NeurIPS 2015 Particle Gibbs with Ancestor Sampling for Probabilistic Programs AISTATS 2015