Bayesian Learning

EDML for Learning Parameters in Directed and Undirected Graphical Models NeurIPS 2013 Efficient Online Inference for Bayesian Nonparametric Relational Models NeurIPS 2013 Exact Learning of Bounded Tree-width Bayesian Networks AISTATS 2013 Exploring the Mind: Integrating Questionnaires and fMRI ICML 2013 Factorial Multi-Task Learning : A Bayesian Nonparametric Approach ICML 2013 Factorized Asymptotic Bayesian Inference for Latent Feature Models NeurIPS 2013 Forgetful Bayes and myopic planning: Human learning and decision-making in a bandit setting NeurIPS 2013 Gaussian Process Conditional Copulas with Applications to Financial Time Series NeurIPS 2013 Gaussian Process Vine Copulas for Multivariate Dependence ICML 2013 Global Solver and Its Efficient Approximation for Variational Bayesian Low-rank Subspace Clustering NeurIPS 2013 GPstuff: Bayesian Modeling with Gaussian Processes JMLR 2013 Hierarchically-coupled hidden Markov models for learning kinetic rates from single-molecule data ICML 2013 High-Dimensional Gaussian Process Bandits NeurIPS 2013 Infinite Markov-Switching Maximum Entropy Discrimination Machines ICML 2013 Integrated Non-Factorized Variational Inference NeurIPS 2013 It is all in the noise: Efficient multi-task Gaussian process inference with structured residuals NeurIPS 2013 Kernelized Bayesian Matrix Factorization ICML 2013 Language-Motivated Approaches to Action Recognition JMLR 2013 Learning Efficient Random Maximum A-Posteriori Predictors with Non-Decomposable Loss Functions NeurIPS 2013 Learning Feature Selection Dependencies in Multi-task Learning NeurIPS 2013 Learning Linear Bayesian Networks with Latent Variables ICML 2013 Learning Stochastic Inverses NeurIPS 2013 Locally Adaptive Bayesian Multivariate Time Series NeurIPS 2013 Low-rank matrix reconstruction and clustering via approximate message passing NeurIPS 2013 Machine Teaching for Bayesian Learners in the Exponential Family NeurIPS 2013