Bayesian Inference

Learning Gaussian Graphical Models with Observed or Latent FVSs NeurIPS 2013 Learning Stochastic Inverses NeurIPS 2013 Learning to Pass Expectation Propagation Messages NeurIPS 2013 Lexical and Hierarchical Topic Regression NeurIPS 2013 Locally Adaptive Bayesian Multivariate Time Series NeurIPS 2013 Lost! Leveraging the Crowd for Probabilistic Visual Self-Localization CVPR 2013 Low-rank matrix reconstruction and clustering via approximate message passing NeurIPS 2013 Machine Teaching for Bayesian Learners in the Exponential Family NeurIPS 2013 MAD-Bayes: MAP-based Asymptotic Derivations from Bayes ICML 2013 Markov Network-Based Unified Classifier for Face Identification ICCV 2013 Memoized Online Variational Inference for Dirichlet Process Mixture Models NeurIPS 2013 Message Passing Inference with Chemical Reaction Networks NeurIPS 2013 Message passing with l1 penalized KL minimization ICML 2013 Minimum Uncertainty Gap for Robust Visual Tracking CVPR 2013 (More) Efficient Reinforcement Learning via Posterior Sampling NeurIPS 2013 Multi-image Blind Deblurring Using a Coupled Adaptive Sparse Prior CVPR 2013 Multiscale Dictionary Learning for Estimating Conditional Distributions NeurIPS 2013 Multi-Task Bayesian Optimization NeurIPS 2013 Multi-task Sparse Learning with Beta Process Prior for Action Recognition CVPR 2013 Nested Expectation Propagation for Gaussian Process Classification with a Multinomial Probit Likelihood JMLR 2013 Nonparametric Multi-group Membership Model for Dynamic Networks NeurIPS 2013 Non-Uniform Camera Shake Removal Using a Spatially-Adaptive Sparse Penalty NeurIPS 2013 ODE parameter inference using adaptive gradient matching with Gaussian processes AISTATS 2013 Online Learning of Nonparametric Mixture Models via Sequential Variational Approximation NeurIPS 2013 Online Variational Approximations to non-Exponential Family Change Point Models: With Application to Radar Tracking NeurIPS 2013