Sampling

Embed and Project: Discrete Sampling with Universal Hashing NeurIPS 2013 Fast Determinantal Point Process Sampling with Application to Clustering NeurIPS 2013 Flexible sampling of discrete data correlations without the marginal distributions NeurIPS 2013 Low-Rank Matrix and Tensor Completion via Adaptive Sampling NeurIPS 2013 Near-Optimal Entrywise Sampling for Data Matrices NeurIPS 2013 Rapid Distance-Based Outlier Detection via Sampling NeurIPS 2013 What do row and column marginals reveal about your dataset? NeurIPS 2013 Continuous Relaxations for Discrete Hamiltonian Monte Carlo NeurIPS 2012 Dynamic Pruning of Factor Graphs for Maximum Marginal Prediction NeurIPS 2012 Efficient Sampling for Bipartite Matching Problems NeurIPS 2012 On Lifting the Gibbs Sampling Algorithm NeurIPS 2012 Accelerated Adaptive Markov Chain for Partition Function Computation NeurIPS 2011 Boosting with Maximum Adaptive Sampling NeurIPS 2011 Finite Time Analysis of Stratified Sampling for Monte Carlo NeurIPS 2011 Simultaneous Sampling and Multi-Structure Fitting with Adaptive Reversible Jump MCMC NeurIPS 2011 Batch Bayesian Optimization via Simulation Matching NeurIPS 2010 Computing Marginal Distributions over Continuous Markov Networks for Statistical Relational Learning NeurIPS 2010 Monte-Carlo Planning in Large POMDPs NeurIPS 2010 Neural Implementation of Hierarchical Bayesian Inference by Importance Sampling NeurIPS 2009 Particle-based Variational Inference for Continuous Systems NeurIPS 2009 An Efficient Sequential Monte Carlo Algorithm for Coalescent Clustering NeurIPS 2008 Reinforcement Learning in Continuous Action Spaces through Sequential Monte Carlo Methods NeurIPS 2007 Ultrafast Monte Carlo for Statistical Summations NeurIPS 2007 Conditional Random Sampling: A Sketch-based Sampling Technique for Sparse Data NeurIPS 2006 Near-Uniform Sampling of Combinatorial Spaces Using XOR Constraints NeurIPS 2006