Bayesian Learning

Online Learning of a Dirichlet Process Mixture of Generalized Dirichlet Distributions for Simultaneous Clustering and Localized Feature Selection ACML 2012 PAC-Bayesian Bound for Gaussian Process Regression and Multiple Kernel Additive Model COLT 2012 Random function priors for exchangeable arrays with applications to graphs and relational data NeurIPS 2012 Scalable imputation of genetic data with a discrete fragmentation-coagulation process NeurIPS 2012 Small-Variance Asymptotics for Exponential Family Dirichlet Process Mixture Models NeurIPS 2012 Sparse Additive Matrix Factorization for Robust PCA and Its Generalization ACML 2012 Stick-Breaking Beta Processes and the Poisson Process AISTATS 2012 The Optimality of Jeffreys Prior for Online Density Estimation and the Asymptotic Normality of Maximum Likelihood Estimators COLT 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 Matching ACML 2012 A Dynamic Relational Infinite Feature Model for Longitudinal Social Networks AISTATS 2011 Bagged Structure Learning of Bayesian Network AISTATS 2011 Bayesian Hierarchical Cross-Clustering AISTATS 2011 Bayesian Inference for Statistical Abduction Using Markov Chain Monte Carlo ACML 2011 Bounds on Individual Risk for Log-loss Predictors COLT 2011 Clustering via Dirichlet Process Mixture Models for Portable Skill Discovery NeurIPS 2011 Crowdclustering NeurIPS 2011 Dependent Hierarchical Beta Process for Image Interpolation and Denoising AISTATS 2011 EigenNet: A Bayesian hybrid of generative and conditional models for sparse learning NeurIPS 2011 Generalized Beta Mixtures of Gaussians NeurIPS 2011 Hierarchical Topic Modeling for Analysis of Time-Evolving Personal Choices NeurIPS 2011 Inferring Interaction Networks using the IBP applied to microRNA Target Prediction NeurIPS 2011 Learning to Learn with Compound HD Models NeurIPS 2011