Bayesian Inference

Kernel Belief Propagation AISTATS 2011 Kernel Embeddings of Latent Tree Graphical Models NeurIPS 2011 Learning mixtures of Gaussians with maximum-a-posteriori oracle AISTATS 2011 Learning unbelievable probabilities NeurIPS 2011 Lightweight Implementations of Probabilistic Programming Languages Via Transformational Compilation AISTATS 2011 Logistic Stick-Breaking Process JMLR 2011 MAP Inference for Bayesian Inverse Reinforcement Learning NeurIPS 2011 Maximum Likelihood vs. Sequential Normalized Maximum Likelihood in On-line Density Estimation COLT 2011 Message-Passing for Approximate MAP Inference with Latent Variables NeurIPS 2011 Minimax Algorithm for Learning Rotations COLT 2011 Mixability is Bayes Risk Curvature Relative to Log Loss COLT 2011 Model-Based Proprioceptive State Estimation for Spring-Mass Running RSS 2011 Modelling Genetic Variations using Fragmentation-Coagulation Processes NeurIPS 2011 Multicore Gibbs Sampling in Dense, Unstructured Graphs AISTATS 2011 Neural Reconstruction with Approximate Message Passing (NeuRAMP) NeurIPS 2011 Non-conjugate Variational Message Passing for Multinomial and Binary Regression NeurIPS 2011 Non-Parametric Estimation of Topic Hierarchies from Texts with Hierarchical Dirichlet Processes JMLR 2011 Nonstandard Interpretations of Probabilistic Programs for Efficient Inference NeurIPS 2011 Online Variational Inference for the Hierarchical Dirichlet Process AISTATS 2011 On the Analysis of Multi-Channel Neural Spike Data NeurIPS 2011 On Tracking The Partition Function NeurIPS 2011 Optimal and Robust Price Experimentation: Learning by Lottery AISTATS 2011 PAC-Bayesian Analysis of Contextual Bandits NeurIPS 2011 Parallel Gibbs Sampling: From Colored Fields to Thin Junction Trees AISTATS 2011 Polytope samplers for inference in ill-posed inverse problems AISTATS 2011