Image de couverture de livre

A Simple Finite-Time Analysis of TD Learning with Linear Function Approximation

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteur principal:	Mitra, Aritra
Format:	Preprint
Publié:	2024
Sujets:	Machine Learning Systems and Control Optimization and Control
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Adversarially-Robust TD Learning with Markovian Data: Finite-Time Rates and Fundamental Limits
par: Maity, Sreejeet, et autres
Publié: (2025)

Finite-Time Analysis of On-Policy Heterogeneous Federated Reinforcement Learning
par: Zhang, Chenyu, et autres
Publié: (2024)

Achieving Tighter Finite-Time Rates for Heterogeneous Federated Stochastic Approximation under Markovian Sampling
par: Zhu, Feng, et autres
Publié: (2025)

Outlier-Robust Linear System Identification Under Heavy-tailed Noise
par: Kanakeri, Vinay, et autres
Publié: (2024)

Model-Free Learning for the Linear Quadratic Regulator over Rate-Limited Channels
par: Ye, Lintao, et autres
Publié: (2024)

A Finite-Time Analysis of TD Learning with Linear Function Approximation without Projections or Strong Convexity
par: Lee, Wei-Cheng, et autres
Publié: (2025)

Robust Q-Learning under Corrupted Rewards
par: Maity, Sreejeet, et autres
Publié: (2024)

Corruption-Tolerant Asynchronous Q-Learning with Near-Optimal Rates
par: Maity, Sreejeet, et autres
Publié: (2025)

Boosting-Enabled Robust System Identification of Partially Observed LTI Systems Under Heavy-Tailed Noise
par: Kanakeri, Vinay, et autres
Publié: (2025)

A Short and Unified Convergence Analysis of the SAG, SAGA, and IAG Algorithms
par: Zhu, Feng, et autres
Publié: (2026)

Stochastic Approximation with Delayed Updates: Finite-Time Rates under Markovian Sampling
par: Adibi, Arman, et autres
Publié: (2024)

Tight Finite Time Bounds of Two-Time-Scale Linear Stochastic Approximation with Markovian Noise
par: Haque, Shaan Ul, et autres
Publié: (2023)

$O(1/k)$ Finite-Time Bound for Non-Linear Two-Time-Scale Stochastic Approximation
par: Chandak, Siddharth
Publié: (2025)

Towards Fast Rates for Federated and Multi-Task Reinforcement Learning
par: Zhu, Feng, et autres
Publié: (2024)

Federated Temporal Difference Learning with Linear Function Approximation under Environmental Heterogeneity
par: Wang, Han, et autres
Publié: (2023)

Heavy-Tailed and Long-Range Dependent Noise in Stochastic Approximation: A Finite-Time Analysis
par: Chandak, Siddharth, et autres
Publié: (2026)

Temporal Difference Learning with Compressed Updates: Error-Feedback meets Reinforcement Learning
par: Mitra, Aritra, et autres
Publié: (2023)

Harnessing Data from Clustered LQR Systems: Personalized and Collaborative Policy Optimization
par: Kanakeri, Vinay, et autres
Publié: (2025)

Finite-Time Bounds for Two-Time-Scale Stochastic Approximation with Arbitrary Norm Contractions and Markovian Noise
par: Chandak, Siddharth, et autres
Publié: (2025)

Learning POMDPs with Linear Function Approximation and Finite Memory
par: Kara, Ali Devran
Publié: (2025)

SCAFFLSA: Taming Heterogeneity in Federated Linear Stochastic Approximation and TD Learning
par: Mangold, Paul, et autres
Publié: (2024)

Rates of Convergence in the Central Limit Theorem for Markov Chains, with an Application to TD Learning
par: Srikant, R.
Publié: (2024)

DASA: Delay-Adaptive Multi-Agent Stochastic Approximation
par: Fabbro, Nicolò Dal, et autres
Publié: (2024)

Predictor-Based Output-Feedback Control of Linear Systems with Time-Varying Input and Measurement Delays via Neural-Approximated Prediction Horizons
par: Bhan, Luke, et autres
Publié: (2026)

Analysis of Off-Policy Multi-Step TD-Learning with Linear Function Approximation
par: Lee, Donghwan
Publié: (2024)

Two-Timescale Linear Stochastic Approximation: Constant Stepsizes Go a Long Way
par: Kwon, Jeongyeol, et autres
Publié: (2024)

Mutual Information Optimal Control of Discrete-Time Linear Systems
par: Enami, Shoju, et autres
Publié: (2025)

Learning to Sparsify Stochastic Linear Bandits
par: Wang, Zhengmiao, et autres
Publié: (2026)

Learning Linear Dynamics from Bilinear Observations
par: Sattar, Yahya, et autres
Publié: (2024)

Sample Complexity of the Linear Quadratic Regulator: A Reinforcement Learning Lens
par: Moghaddam, Amirreza Neshaei, et autres
Publié: (2024)

Learning Decentralized Linear Quadratic Regulators with $\sqrt{T}$ Regret
par: Ye, Lintao, et autres
Publié: (2022)

Regret Analysis of Policy Optimization over Submanifolds for Linearly Constrained Online LQG
par: Chang, Ting-Jui, et autres
Publié: (2024)

Fixed Horizon Linear Quadratic Covariance Steering in Continuous Time with Hilbert-Schmidt Terminal Cost
par: Sial, Tushar, et autres
Publié: (2025)

Certified Approximate Reachability (CARe): Formal Error Bounds on Deep Learning of Reachable Sets
par: Solanki, Prashant, et autres
Publié: (2025)

Online Reinforcement Learning in Markov Decision Process Using Linear Programming
par: Leon, Vincent, et autres
Publié: (2023)

Fitted Q-Iteration via Max-Plus-Linear Approximation
par: Liu, Y., et autres
Publié: (2024)

Learning of Linear Dynamical Systems as a Non-Commutative Polynomial Optimization Problem
par: Zhou, Quan, et autres
Publié: (2020)

Cost-Driven Representation Learning for Linear Quadratic Gaussian Control: Part I
par: Tian, Yi, et autres
Publié: (2022)

Cost-Driven Representation Learning for Linear Quadratic Gaussian Control: Part II
par: Tian, Yi, et autres
Publié: (2026)

Finite Sample Frequency Domain Identification
par: Tsiamis, Anastasios, et autres
Publié: (2024)