variance reduction

Unbiased Generative Semi-Supervised Learning JMLR 2014 Accelerating Stochastic Gradient Descent using Predictive Variance Reduction NeurIPS 2013 B-test: A Non-parametric, Low Variance Kernel Two-sample Test NeurIPS 2013 Near-Optimal Bounds for Cross-Validation via Loss Stability ICML 2013 Toward Optimal Stratification for Stratified Monte-Carlo Integration ICML 2013 Variance Reduction for Stochastic Gradient Optimization NeurIPS 2013 Adaptive Stratified Sampling for Monte-Carlo integration of Differentiable functions NeurIPS 2012 Analysis and Improvement of Policy Gradient Estimation NeurIPS 2011 Improving Policy Gradient Estimates with Influence Information ACML 2011 Variance Penalizing AdaBoost NeurIPS 2011 Variance Reduction in Monte-Carlo Tree Search NeurIPS 2011 On Combining Graph-based Variance Reduction schemes AISTATS 2010 A Generalized Natural Actor-Critic Algorithm NeurIPS 2009 An Efficient Sequential Monte Carlo Algorithm for Coalescent Clustering NeurIPS 2008 Particle Filter-based Policy Gradient in POMDPs NeurIPS 2008 Signal-to-Noise Ratio Analysis of Policy Gradient Algorithms NeurIPS 2008 Bayesian Policy Gradient Algorithms NeurIPS 2006 Geometric Variance Reduction in Markov Chains: Application to Value Function and Gradient Estimation JMLR 2006 Variance Reduction Techniques for Gradient Estimates in Reinforcement Learning JMLR 2004