Bayesian Inference

Tree-Structured Stick Breaking for Hierarchical Data NeurIPS 2010 Variational bounds for mixed-data factor analysis NeurIPS 2010 Variational Inference over Combinatorial Spaces NeurIPS 2010 Variational methods for Reinforcement Learning AISTATS 2010 Variational Relevance Vector Machine for Tabular Data ACML 2010 Why are DBNs sparse? AISTATS 2010 L_1-Penalized Robust Estimation for a Class of Inverse Problems Arising in Multiview Geometry NeurIPS 2009 A Bayesian Analysis of Dynamics in Free Recall NeurIPS 2009 A Bayesian Model for Simultaneous Image Clustering, Annotation and Object Segmentation NeurIPS 2009 Accelerating Bayesian Structural Inference for Non-Decomposable Gaussian Graphical Models NeurIPS 2009 Adaptive Design Optimization in Experiments with People NeurIPS 2009 An Algorithm for Reading Dependencies from the Minimal Undirected Independence Map of a Graphoid that Satisfies Weak Transitivity JMLR 2009 A Neural Implementation of the Kalman Filter NeurIPS 2009 A Parameter-Free Classification Method for Large Scale Learning JMLR 2009 Application of Non Parametric Empirical Bayes Estimation to High Dimensional Classification JMLR 2009 Approximating MAP by Compensating for Structural Relaxations NeurIPS 2009 A Stochastic approximation method for inference in probabilistic graphical models NeurIPS 2009 Asymptotic Analysis of MAP Estimation via the Replica Method and Compressed Sensing NeurIPS 2009 Bayesian estimation of orientation preference maps NeurIPS 2009 Bayesian Nonparametric Models on Decomposable Graphs NeurIPS 2009 Bayesian Source Localization with the Multivariate Laplace Prior NeurIPS 2009 Bayesian Sparse Factor Models and DAGs Inference and Comparison NeurIPS 2009 Clustering sequence sets for motif discovery NeurIPS 2009 Construction of Nonparametric Bayesian Models from Parametric Bayes Equations NeurIPS 2009 Controlling the False Discovery Rate of the Association/Causality Structure Learned with the PC Algorithm JMLR 2009