conftrace_

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

Communication-Efficient Distributed Optimization in Networks with Gradient Tracking and Variance Reduction JMLR 2020
Amortized variance reduction for doubly stochastic objective UAI 2020
Quantized Compressive Sampling of Stochastic Gradients for Efficient Communication in Distributed Deep Learning AAAI 2020
Variance Reduction via Accelerated Dual Averaging for Finite-Sum Optimization NIPS 2020
Variance reduction for Random Coordinate Descent-Langevin Monte Carlo NIPS 2020
A Catalyst Framework for Minimax Optimization NIPS 2020
Adaptive Importance Sampling for Finite-Sum Optimization and Sampling with Decreasing Step-Sizes NIPS 2020
Random Reshuffling: Simple Analysis with Vast Improvements NIPS 2020
DisARM: An Antithetic Gradient Estimator for Binary Latent Variables NIPS 2020
Spectral Subsampling MCMC for Stationary Time Series ICML 2020
Conditional gradient methods for stochastically constrained convex minimization ICML 2020
Variance Reduction in Stochastic Particle-Optimization Sampling ICML 2020
Amortized Nesterov’s Momentum: A Robust Momentum and Its Application to Deep Learning UAI 2020
An $\widetilde\mathcal{O}(m/\varepsilon^3.5)$-Cost Algorithm for Semidefinite Programs with Diagonal Constraints COLT 2020
A Rule for Gradient Estimator Selection, with an Application to Variational Inference AISTATS 2020
On the Convergence of SARAH and Beyond AISTATS 2020
Discrete Action On-Policy Learning with Action-Value Critic AISTATS 2020
Practical Nonisotropic Monte Carlo Sampling in High Dimensions via Determinantal Point Processes AISTATS 2020
Variance Reduction for Evolution Strategies via Structured Control Variates AISTATS 2020
Hamiltonian Monte Carlo Swindles AISTATS 2020
Stochastic Variance-Reduced Algorithms for PCA with Arbitrary Mini-Batch Sizes AISTATS 2020
A Hybrid Stochastic Policy Gradient Algorithm for Reinforcement Learning AISTATS 2020
A Unified Theory of SGD: Variance Reduction, Sampling, Quantization and Coordinate Descent AISTATS 2020
Communication-Efficient Distributed Optimization in Networks with Gradient Tracking and Variance Reduction AISTATS 2020
Global Convergence and Variance Reduction for a Class of Nonconvex-Nonconcave Minimax Problems NIPS 2020