importance sampling

Doubly Robust Off-policy Value Evaluation for Reinforcement Learning ICML 2016 Gradient-based Sampling: An Adaptive Importance Sampling for Least-squares NeurIPS 2016 Importance Sampling Tree for Large-scale Empirical Expectation ICML 2016 Importance Weighting Without Importance Weights: An Efficient Algorithm for Combinatorial Semi-Bandits JMLR 2016 Measuring the reliability of MCMC inference with bidirectional Monte Carlo NeurIPS 2016 Neurally-Guided Procedural Models: Amortized Inference for Procedural Graphics Programs using Neural Networks NeurIPS 2016 Partition Functions from Rao-Blackwellized Tempered Sampling ICML 2016 Semi-Supervised Training in Deep Learning Acoustic Model Interspeech 2016 Structure Discovery in Bayesian Networks by Sampling Partial Orders JMLR 2016 Sublinear Time Orthogonal Tensor Decomposition NeurIPS 2016 Variational Inference for Monte Carlo Objectives ICML 2016 Active Pointillistic Pattern Search AISTATS 2015 A Statistical Perspective on Algorithmic Leveraging JMLR 2015 Bounding the Cost of Search-Based Lifted Inference NeurIPS 2015 Counterfactual Risk Minimization: Learning from Logged Bandit Feedback ICML 2015 Probabilistic Variational Bounds for Graphical Models NeurIPS 2015 Quartz: Randomized Dual Coordinate Ascent with Arbitrary Sampling NeurIPS 2015 Stochastic Dual Coordinate Ascent with Adaptive Probabilities ICML 2015 Stochastic Optimization with Importance Sampling for Regularized Loss Minimization ICML 2015 Variance Reduction via Antithetic Markov Chains AISTATS 2015 A* Sampling NeurIPS 2014 A Statistical Perspective on Algorithmic Leveraging ICML 2014 Instance-weighted Transfer Learning of Active Appearance Models CVPR 2014 Scaling-up Importance Sampling for Markov Logic Networks NeurIPS 2014 Stochastic Gradient Descent, Weighted Sampling, and the Randomized Kaczmarz algorithm NeurIPS 2014