Bayesian Inference

PAC-Bayes Risk Bounds for Stochastic Averages and Majority Votes of Sample-Compressed Classifiers JMLR 2007 Preventing Over-Fitting during Model Selection via Bayesian Regularisation of the Hyper-Parameters JMLR 2007 Privacy-Preserving Belief Propagation and Sampling NeurIPS 2007 Regulator Discovery from Gene Expression Time Series of Malaria Parasites: a Hierachical Approach NeurIPS 2007 Robust Regression with Twinned Gaussian Processes NeurIPS 2007 Sequential Hypothesis Testing under Stochastic Deadlines NeurIPS 2007 Simultaneous Localisation and Mapping in Dynamic Environments (SLAMIDE) with Reversible Data Associa RSS 2007 The Generalized FITC Approximation NeurIPS 2007 The Infinite Gamma-Poisson Feature Model NeurIPS 2007 The Infinite Markov Model NeurIPS 2007 The rat as particle filter NeurIPS 2007 TrueSkill Through Time: Revisiting the History of Chess NeurIPS 2007 Variational Inference for Diffusion Processes NeurIPS 2007 Variational inference for Markov jump processes NeurIPS 2007 A Bayesian Approach to Diffusion Models of Decision-Making and Response Time NeurIPS 2006 A Bayesian Approach to Nonlinear Parameter Identification for Rigid Body Dynamics RSS 2006 Accelerated Variational Dirichlet Process Mixtures NeurIPS 2006 A Collapsed Variational Bayesian Inference Algorithm for Latent Dirichlet Allocation NeurIPS 2006 Aggregating Classification Accuracy across Time: Application to Single Trial EEG NeurIPS 2006 Analysis of Empirical Bayesian Methods for Neuroelectromagnetic Source Localization NeurIPS 2006 An Information Theoretic Framework for Eukaryotic Gradient Sensing NeurIPS 2006 A Nonparametric Bayesian Method for Inferring Features From Similarity Judgments NeurIPS 2006 A Novel Gaussian Sum Smoother for Approximate Inference in Switching Linear Dynamical Systems NeurIPS 2006 A PAC-Bayes Risk Bound for General Loss Functions NeurIPS 2006 Approximate inference using planar graph decomposition NeurIPS 2006