stochastic approximation

Statistical inference with implicit SGD: proximal Robbins-Monro vs. Polyak-Ruppert ICML 2022 The Dynamics of Riemannian Robbins-Monro Algorithms COLT 2022 A Law of Iterated Logarithm for Multi-Agent Reinforcement Learning NeurIPS 2021 An Inertial Newton Algorithm for Deep Learning JMLR 2021 Convergence Properties of Stochastic Hypergradients AISTATS 2021 Fast Learning for Renewal Optimization in Online Task Scheduling JMLR 2021 Finite-Sample Analysis of Off-Policy TD-Learning via Generalized Bellman Operators NeurIPS 2021 Kernel Distributionally Robust Optimization: Generalized Duality Theorem and Stochastic Approximation AISTATS 2021 Logical Team Q-learning: An approach towards factored policies in cooperative MARL AISTATS 2021 Nonlinear Two-Time-Scale Stochastic Approximation: Convergence and Finite-Time Performance L4DC 2021 On Riemannian Stochastic Approximation Schemes with Fixed Step-Size AISTATS 2021 On the Stability of Random Matrix Product with Markovian Noise: Application to Linear Stochastic Approximation and TD Learning COLT 2021 Robust Reinforcement Learning using Least Squares Policy Iteration with Provable Performance Guarantees ICML 2021 Sample Complexity Bounds for Two Timescale Value-based Reinforcement Learning Algorithms AISTATS 2021 Simple combinatorial algorithms for combinatorial bandits: corruptions and approximations UAI 2021 Stochastic Approximation for Online Tensorial Independent Component Analysis COLT 2021 A mathematical model for automatic differentiation in machine learning NeurIPS 2020 A Tale of Two-Timescale Reinforcement Learning with the Tightest Finite-Time Bound AAAI 2020 Explicit Mean-Square Error Bounds for Monte-Carlo and Linear Stochastic Approximation AISTATS 2020 Exploiting Higher Order Smoothness in Derivative-free Optimization and Continuous Bandits NeurIPS 2020 Finite-Sample Analysis of Contractive Stochastic Approximation Using Smooth Convex Envelopes NeurIPS 2020 Finite-Time Analysis for Double Q-learning NeurIPS 2020 Finite-Time Analysis of Asynchronous Stochastic Approximation and Q-Learning COLT 2020 Finite-Time Error Bounds for Biased Stochastic Approximation with Applications to Q-Learning AISTATS 2020 Finite-Time Performance of Distributed Two-Time-Scale Stochastic Approximation L4DC 2020