Markov Chain Monte Carlo

Perceptual Multistability as Markov Chain Monte Carlo Inference NeurIPS 2009 Randomized Pruning: Efficiently Calculating Expectations in Large Dynamic Programs NeurIPS 2009 Sharing Features among Dynamical Systems with Beta Processes NeurIPS 2009 The Wisdom of Crowds in the Recollection of Order Information NeurIPS 2009 A ``Shape Aware'' Model for semi-supervised Learning of Objects and its Context NeurIPS 2008 Asynchronous Distributed Learning of Topic Models NeurIPS 2008 Efficient Inference in Phylogenetic InDel Trees NeurIPS 2008 Efficient Sampling for Gaussian Process Inference using Control Variables NeurIPS 2008 Evaluating probabilities under high-dimensional latent variable models NeurIPS 2008 Non-stationary dynamic Bayesian networks NeurIPS 2008 Stochastic Relational Models for Large-scale Dyadic Data using MCMC NeurIPS 2008 Bayesian Agglomerative Clustering with Coalescents NeurIPS 2007 Bayesian Policy Learning with Trans-Dimensional MCMC NeurIPS 2007 Markov Chain Monte Carlo with People NeurIPS 2007 Privacy-Preserving Belief Propagation and Sampling NeurIPS 2007 Simulated Annealing: Rigorous finite-time guarantees for optimization on continuous domains NeurIPS 2007 The Infinite Gamma-Poisson Feature Model NeurIPS 2007 The rat as particle filter NeurIPS 2007 Bayesian Ensemble Learning NeurIPS 2006 Conditional mean field NeurIPS 2006 Hidden Markov Dirichlet Process: Modeling Genetic Recombination in Open Ancestral Space 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