markov chain monte carlo

Non-stationary dynamic Bayesian networks NeurIPS 2008 Stochastic Relational Models for Large-scale Dyadic Data using MCMC NeurIPS 2008 The Gaussian Process Density Sampler NeurIPS 2008 Bayesian Policy Learning with Trans-Dimensional MCMC NeurIPS 2007 Collective Inference on Markov Models for Modeling Bird Migration NeurIPS 2007 Markov Chain Monte Carlo with People NeurIPS 2007 Multi-Task Learning for Classification with Dirichlet Process Priors JMLR 2007 Semantic Modeling of Places using Objects RSS 2007 Simulated Annealing: Rigorous finite-time guarantees for optimization on continuous domains NeurIPS 2007 The Infinite Gamma-Poisson Feature Model NeurIPS 2007 Adaptor Grammars: A Framework for Specifying Compositional Nonparametric Bayesian Models NeurIPS 2006 Bayesian Ensemble Learning NeurIPS 2006 Hierarchical Dirichlet Processes with Random Effects NeurIPS 2006 Learning annotated hierarchies from relational data NeurIPS 2006 Near-Uniform Sampling of Combinatorial Spaces Using XOR Constraints NeurIPS 2006 A Bayesian Model for Supervised Clustering with the Dirichlet Process Prior JMLR 2005 Assessing Approximate Inference for Binary Gaussian Process Classification JMLR 2005 Reinforcement Learning with Factored States and Actions JMLR 2004 On Inclusion-Driven Learning of Bayesian Networks JMLR 2003