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Sampling

101 papers

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Papers

Importance sampling for unbiased on-demand evaluation of knowledge base population EMNLP 2017
Learning Determinantal Point Processes with Moments and Cycles ICML 2017
Towards Unifying Hamiltonian Monte Carlo and Slice Sampling NIPS 2016
Kronecker Determinantal Point Processes NIPS 2016
Measuring Sample Quality with Stein's Method NIPS 2015
Reflection, Refraction, and Hamiltonian Monte Carlo NIPS 2015
Neural Adaptive Sequential Monte Carlo NIPS 2015
Fast Bidirectional Probability Estimation in Markov Models NIPS 2015
A* Sampling NIPS 2014
Approximate Slice Sampling for Bayesian Posterior Inference AISTATS 2014
Fast Determinantal Point Process Sampling with Application to Clustering NIPS 2013
Approximate Inference in Continuous Determinantal Processes NIPS 2013
Embed and Project: Discrete Sampling with Universal Hashing NIPS 2013
Flexible sampling of discrete data correlations without the marginal distributions NIPS 2013
What do row and column marginals reveal about your dataset? NIPS 2013
Rapid Distance-Based Outlier Detection via Sampling NIPS 2013
Efficient Sampling for Bipartite Matching Problems NIPS 2012
Dynamic Pruning of Factor Graphs for Maximum Marginal Prediction NIPS 2012
Continuous Relaxations for Discrete Hamiltonian Monte Carlo NIPS 2012
On Lifting the Gibbs Sampling Algorithm NIPS 2012
Accelerated Adaptive Markov Chain for Partition Function Computation NIPS 2011
Simultaneous Sampling and Multi-Structure Fitting with Adaptive Reversible Jump MCMC NIPS 2011
Computing Marginal Distributions over Continuous Markov Networks for Statistical Relational Learning NIPS 2010
Particle-based Variational Inference for Continuous Systems NIPS 2009
Near-Uniform Sampling of Combinatorial Spaces Using XOR Constraints NIPS 2006