Bayesian Learning

Multiresolution Gaussian Processes NeurIPS 2012 Nonparametric Bayesian Inverse Reinforcement Learning for Multiple Reward Functions NeurIPS 2012 Nonparametric Bayesian Models for Unsupervised Scene Analysis and Reconstruction RSS 2012 Nonparametric Max-Margin Matrix Factorization for Collaborative Prediction NeurIPS 2012 Perfect Dimensionality Recovery by Variational Bayesian PCA NeurIPS 2012 Practical Bayesian Optimization of Machine Learning Algorithms NeurIPS 2012 Putting Bayes to sleep NeurIPS 2012 Random function priors for exchangeable arrays with applications to graphs and relational data NeurIPS 2012 Random Utility Theory for Social Choice NeurIPS 2012 Repulsive Mixtures NeurIPS 2012 Scalable imputation of genetic data with a discrete fragmentation-coagulation process NeurIPS 2012 Slice sampling normalized kernel-weighted completely random measure mixture models NeurIPS 2012 Small-Variance Asymptotics for Exponential Family Dirichlet Process Mixture Models NeurIPS 2012 Stick-Breaking Beta Processes and the Poisson Process AISTATS 2012 Strategic Impatience in Go/NoGo versus Forced-Choice Decision-Making NeurIPS 2012 The Time-Marginalized Coalescent Prior for Hierarchical Clustering NeurIPS 2012 Truly Nonparametric Online Variational Inference for Hierarchical Dirichlet Processes NeurIPS 2012 Truncation-free Online Variational Inference for Bayesian Nonparametric Models NeurIPS 2012 Variational Bayesian Optimization for Runtime Risk-Sensitive Control RSS 2012 A Bayesian Approach for Learning and Planning in Partially Observable Markov Decision Processes JMLR 2011 Active learning of neural response functions with Gaussian processes NeurIPS 2011 Additive Gaussian Processes NeurIPS 2011 A Global Structural EM Algorithm for a Model of Cancer Progression NeurIPS 2011 A Model for Temporal Dependencies in Event Streams NeurIPS 2011 Analytical Results for the Error in Filtering of Gaussian Processes NeurIPS 2011