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

Convergence of mean-field Langevin dynamics: time-space discretization, stochastic gradient, and variance reduction NIPS 2023
Quantum speedups for stochastic optimization NIPS 2023
Double Doubly Robust Thompson Sampling for Generalized Linear Contextual Bandits AAAI 2023
Cyclic Block Coordinate Descent With Variance Reduction for Composite Nonconvex Optimization ICML 2023
Faster Gradient-Free Algorithms for Nonsmooth Nonconvex Stochastic Optimization ICML 2023
Generalized-Smooth Nonconvex Optimization is As Efficient As Smooth Nonconvex Optimization ICML 2023
Private (Stochastic) Non-Convex Optimization Revisited: Second-Order Stationary Points and Excess Risks NIPS 2023
Accelerated Cyclic Coordinate Dual Averaging with Extrapolation for Composite Convex Optimization ICML 2023
Optimal randomized multilevel Monte Carlo for repeatedly nested expectations ICML 2023
Knowledge Distillation Performs Partial Variance Reduction NIPS 2023
Corruption-Tolerant Algorithms for Generalized Linear Models AAAI 2023
Beyond ADMM: A Unified Client-Variance-Reduced Adaptive Federated Learning Framework AAAI 2023
Regret-Optimal Model-Free Reinforcement Learning for Discounted MDPs with Short Burn-In Time NIPS 2023
Low-Variance Gradient Estimation in Unrolled Computation Graphs with ES-Single ICML 2023
HeteRSGD: Tackling Heterogeneous Sampling Costs via Optimal Reweighted Stochastic Gradient Descent AISTATS 2023
Off-Policy Evaluation for Large Action Spaces via Conjunct Effect Modeling ICML 2023
Projection-Free Methods for Stochastic Simple Bilevel Optimization with Convex Lower-level Problem NIPS 2023
Cold Analysis of Rao-Blackwellized Straight-Through Gumbel-Softmax Gradient Estimator ICML 2023
Zeroth-Order Alternating Gradient Descent Ascent Algorithms for A Class of Nonconvex-Nonconcave Minimax Problems JMLR 2023
Correcting discount-factor mismatch in on-policy policy gradient methods ICML 2023
Theoretical Guarantees of Learning Ensembling Strategies with Applications to Time Series Forecasting ICML 2023
Adaptive SGD with Polyak stepsize and Line-search: Robust Convergence and Variance Reduction NIPS 2023
Improved Powered Stochastic Optimization Algorithms for Large-Scale Machine Learning JMLR 2023
Winner-Take-All Column Row Sampling for Memory Efficient Adaptation of Language Model NIPS 2023
Doubly Robust Stein-Kernelized Monte Carlo Estimator: Simultaneous Bias-Variance Reduction and Supercanonical Convergence JMLR 2023