Bayesian Learning

Scalable Bayesian Low-Rank Decomposition of Incomplete Multiway Tensors ICML 2014 Scalable Collaborative Bayesian Preference Learning AISTATS 2014 Skip Context Tree Switching ICML 2014 SMERED: A Bayesian Approach to Graphical Record Linkage and De-duplication AISTATS 2014 Sparse Bayesian Variable Selection for the Identification of Antigenic Variability in the Foot-and-Mouth Disease Virus AISTATS 2014 Spatio-temporal Representations of Uncertainty in Spiking Neural Networks NeurIPS 2014 Spectral Methods for Indian Buffet Process Inference NeurIPS 2014 Stochastic Regret Minimization via Thompson Sampling COLT 2014 Stochastic variational inference for hidden Markov models NeurIPS 2014 Student-t Processes as Alternatives to Gaussian Processes AISTATS 2014 The Bayesian Case Model: A Generative Approach for Case-Based Reasoning and Prototype Classification NeurIPS 2014 Tilted Variational Bayes AISTATS 2014 Tree-structured Gaussian Process Approximations NeurIPS 2014 Variational Gaussian Process State-Space Models NeurIPS 2014 Active Learning for Probabilistic Hypotheses Using the Maximum Gibbs Error Criterion NeurIPS 2013 Active Visual Recognition with Expertise Estimation in Crowdsourcing ICCV 2013 Adaptive Hamiltonian and Riemann Manifold Monte Carlo ICML 2013 A Framework for Evaluating Approximation Methods for Gaussian Process Regression JMLR 2013 A* Lasso for Learning a Sparse Bayesian Network Structure for Continuous Variables NeurIPS 2013 Annealing between distributions by averaging moments NeurIPS 2013 A Non-parametric Bayesian Network Prior of Human Pose ICCV 2013 Approximate Bayesian Image Interpretation using Generative Probabilistic Graphics Programs NeurIPS 2013 Approximate Gaussian process inference for the drift function in stochastic differential equations NeurIPS 2013 A recursive estimate for the predictive likelihood in a topic model AISTATS 2013 A simple example of Dirichlet process mixture inconsistency for the number of components NeurIPS 2013