Markov Chain Monte Carlo

Ancestor Sampling for Particle Gibbs NeurIPS 2012 Bayesian nonparametric models for bipartite graphs NeurIPS 2012 Bayesian nonparametric models for ranked data NeurIPS 2012 Burn-in, bias, and the rationality of anchoring NeurIPS 2012 Continuous Relaxations for Discrete Hamiltonian Monte Carlo NeurIPS 2012 Dynamic Pruning of Factor Graphs for Maximum Marginal Prediction NeurIPS 2012 Effective Split-Merge Monte Carlo Methods for Nonparametric Models of Sequential Data NeurIPS 2012 Efficient Sampling for Bipartite Matching Problems NeurIPS 2012 Entangled Monte Carlo NeurIPS 2012 FastEx: Hash Clustering with Exponential Families NeurIPS 2012 MCMC for continuous-time discrete-state systems NeurIPS 2012 Monte Carlo Methods for Maximum Margin Supervised Topic Models NeurIPS 2012 Nonparametric Bayesian Inverse Reinforcement Learning for Multiple Reward Functions NeurIPS 2012 On Lifting the Gibbs Sampling Algorithm NeurIPS 2012 Repulsive Mixtures NeurIPS 2012 Slice sampling normalized kernel-weighted completely random measure mixture models NeurIPS 2012 Sparse Approximate Manifolds for Differential Geometric MCMC NeurIPS 2012 The Coloured Noise Expansion and Parameter Estimation of Diffusion Processes NeurIPS 2012 Training sparse natural image models with a fast Gibbs sampler of an extended state space NeurIPS 2012 Why MCA? Nonlinear sparse coding with spike-and-slab prior for neurally plausible image encoding NeurIPS 2012 Accelerated Adaptive Markov Chain for Partition Function Computation NeurIPS 2011 Automated Refinement of Bayes Networks' Parameters based on Test Ordering Constraints NeurIPS 2011 Bayesian Bias Mitigation for Crowdsourcing NeurIPS 2011 Bayesian Partitioning of Large-Scale Distance Data NeurIPS 2011 Collective Graphical Models NeurIPS 2011