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

Sample Complexity of Variance-Reduced Distributionally Robust Q-Learning JMLR 2024
Decentralized Sum-of-Nonconvex Optimization AAAI 2024
Universality of AdaGrad Stepsizes for Stochastic Optimization: Inexact Oracle, Acceleration and Variance Reduction NIPS 2024
Decentralized Natural Policy Gradient with Variance Reduction for Collaborative Multi-Agent Reinforcement Learning JMLR 2024
Adaptive Federated Minimax Optimization with Lower Complexities AISTATS 2024
DISCount: Counting in Large Image Collections with Detector-Based Importance Sampling AAAI 2024
Robust Fine-tuning of Zero-shot Models via Variance Reduction NIPS 2024
A Bregman Proximal Stochastic Gradient Method with Extrapolation for Nonconvex Nonsmooth Problems AAAI 2024
Complexity of Single Loop Algorithms for Nonlinear Programming with Stochastic Objective and Constraints AISTATS 2024
Breaking the Heavy-Tailed Noise Barrier in Stochastic Optimization Problems AISTATS 2024
Vector-Valued Control Variates ICML 2023
Provable Multi-instance Deep AUC Maximization with Stochastic Pooling ICML 2023
HeteRSGD: Tackling Heterogeneous Sampling Costs via Optimal Reweighted Stochastic Gradient Descent AISTATS 2023
Preferential Subsampling for Stochastic Gradient Langevin Dynamics AISTATS 2023
Off-Policy Evaluation for Large Action Spaces via Conjunct Effect Modeling ICML 2023
Low-Variance Gradient Estimation in Unrolled Computation Graphs with ES-Single ICML 2023
Double Doubly Robust Thompson Sampling for Generalized Linear Contextual Bandits AAAI 2023
Stochastic Gradient Descent under Markovian Sampling Schemes ICML 2023
Tighter PAC-Bayes Generalisation Bounds by Leveraging Example Difficulty AISTATS 2023
Model-based Reinforcement Learning with Scalable Composite Policy Gradient Estimators ICML 2023
A Variance-Reduced and Stabilized Proximal Stochastic Gradient Method with Support Identification Guarantees for Structured Optimization AISTATS 2023
Improved Rate of First Order Algorithms for Entropic Optimal Transport AISTATS 2023
AdaGDA: Faster Adaptive Gradient Descent Ascent Methods for Minimax Optimization AISTATS 2023
Theoretical Guarantees of Learning Ensembling Strategies with Applications to Time Series Forecasting ICML 2023
Corruption-Tolerant Algorithms for Generalized Linear Models AAAI 2023