conftrace_

stochastic approximation

101 papers

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Also known as

SA

Co-occurring keywords

convergence rate (607) reinforcement learning (4352) temporal difference learning (149) markov chain (207) finite-time analysis (31) convergence analysis (395) markov decision process (790) convex optimization (1321) online learning (1777) policy evaluation (115)

Papers

On Riemannian Stochastic Approximation Schemes with Fixed Step-Size AISTATS 2021
A Law of Iterated Logarithm for Multi-Agent Reinforcement Learning NIPS 2021
Finite-Sample Analysis of Off-Policy TD-Learning via Generalized Bellman Operators NIPS 2021
Finite-Time Error Bounds for Biased Stochastic Approximation with Applications to Q-Learning AISTATS 2020
Lookahead-Bounded Q-learning ICML 2020
Finite-Time Performance of Distributed Two-Time-Scale Stochastic Approximation L4DC 2020
On the Convergence of Nesterov’s Accelerated Gradient Method in Stochastic Settings ICML 2020
Zap Q-Learning With Nonlinear Function Approximation NIPS 2020
Joint Stochastic Approximation and Its Application to Learning Discrete Latent Variable Models UAI 2020
A Tale of Two-Timescale Reinforcement Learning with the Tightest Finite-Time Bound AAAI 2020
A mathematical model for automatic differentiation in machine learning NIPS 2020
Uncorrected Least-Squares Temporal Difference with Lambda-Return AAAI 2020
Finite-Sample Analysis of Contractive Stochastic Approximation Using Smooth Convex Envelopes NIPS 2020
The Mean-Squared Error of Double Q-Learning NIPS 2020
Finite-Time Analysis of Asynchronous Stochastic Approximation and $Q$-Learning COLT 2020
Exploiting Higher Order Smoothness in Derivative-free Optimization and Continuous Bandits NIPS 2020
Finite-Time Analysis for Double Q-learning NIPS 2020
Explicit Mean-Square Error Bounds for Monte-Carlo and Linear Stochastic Approximation AISTATS 2020
Non-asymptotic Analysis of Biased Stochastic Approximation Scheme COLT 2019
Two Time-scale Off-Policy TD Learning: Non-asymptotic Analysis over Markovian Samples NIPS 2019
Stochastic Approximation of Smooth and Strongly Convex Functions: Beyond the $O(1/T)$ Convergence Rate COLT 2019
On the Global Convergence of (Fast) Incremental Expectation Maximization Methods NIPS 2019
Finite-Sample Analysis for SARSA with Linear Function Approximation NIPS 2019
Finite-Time Performance Bounds and Adaptive Learning Rate Selection for Two Time-Scale Reinforcement Learning NIPS 2019
Finite-Time Error Bounds For Linear Stochastic Approximation andTD Learning COLT 2019