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variance reduction

523 papers

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Also known as

VR

Co-occurring keywords

stochastic optimization (1060) stochastic gradient descent (1091) stochastic gradient (296) reinforcement learning (4352) policy gradient (520) nonconvex optimization (316) gradient estimation (150) non-convex optimization (547) importance sampling (318) control variate (54)

Papers

Improving Sign Random Projections With Additional Information ICML 2018
Variance-Reduced Stochastic Gradient Descent on Streaming Data NIPS 2018
The Mirage of Action-Dependent Baselines in Reinforcement Learning ICML 2018
Stochastic Expectation Maximization with Variance Reduction NIPS 2018
Temporal Regularization for Markov Decision Process NIPS 2018
Joint Active Feature Acquisition and Classification with Variable-Size Set Encoding NIPS 2018
Bayesian Network Classifiers Under the Ensemble Perspective PGM 2018
Using J-K-fold Cross Validation To Reduce Variance When Tuning NLP Models COLING 2018
Stochastic Variance-Reduced Cubic Regularized Newton Methods ICML 2018
Stochastic Variance-Reduced Hamilton Monte Carlo Methods ICML 2018
Stochastic Training of Graph Convolutional Networks with Variance Reduction ICML 2018
Quasi-Monte Carlo Variational Inference ICML 2018
Katyusha: The First Direct Acceleration of Stochastic Gradient Methods JMLR 2018
Breaking the Span Assumption Yields Fast Finite-Sum Minimization NIPS 2018
Variance Reduction in Black-box Variational Inference by Adaptive Importance Sampling IJCAI 2018
On the Theory of Variance Reduction for Stochastic Gradient Monte Carlo ICML 2018
REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models NIPS 2017
Sticking the Landing: Simple, Lower-Variance Gradient Estimators for Variational Inference NIPS 2017
Limitations on Variance-Reduction and Acceleration Schemes for Finite Sums Optimization NIPS 2017
Reducing Reparameterization Gradient Variance NIPS 2017
Fast Stochastic Variance Reduced ADMM for Stochastic Composition Optimization IJCAI 2017
Mini-batch Block-coordinate based Stochastic Average Adjusted Gradient Methods to Solve Big Data Problems ACML 2017
Averaged-DQN: Variance Reduction and Stabilization for Deep Reinforcement Learning ICML 2017
Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms AISTATS 2017
Safe Adaptive Importance Sampling NIPS 2017