Imagen de Portada

Span-Agnostic Optimal Sample Complexity and Oracle Inequalities for Average-Reward RL

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Zurek, Matthew, Chen, Yudong
Formato:	Preprint
Publicado:	2025
Materias:	Machine Learning Information Theory Optimization and Control
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Span-Based Optimal Sample Complexity for Average Reward MDPs
por: Zurek, Matthew, et al.
Publicado: (2023)

Span-Based Optimal Sample Complexity for Weakly Communicating and General Average Reward MDPs
por: Zurek, Matthew, et al.
Publicado: (2024)

Optimal Single-Policy Sample Complexity and Transient Coverage for Average-Reward Offline RL
por: Zurek, Matthew, et al.
Publicado: (2025)

The Plug-in Approach for Average-Reward and Discounted MDPs: Optimal Sample Complexity Analysis
por: Zurek, Matthew, et al.
Publicado: (2024)

Optimal Variance-Dependent Regret Bounds for Infinite-Horizon MDPs
por: Zamir, Guy, et al.
Publicado: (2026)

Gap-Free Clustering: Sensitivity and Robustness of SDP
por: Zurek, Matthew, et al.
Publicado: (2023)

Faster Fixed-Point Methods for Multichain MDPs
por: Zurek, Matthew, et al.
Publicado: (2025)

Is Q-Learning Minimax Optimal? A Tight Sample Complexity Analysis
por: Li, Gen, et al.
Publicado: (2021)

Optimal Sample Complexity for Average Reward Markov Decision Processes
por: Wang, Shengbo, et al.
Publicado: (2023)

Sample Complexity of Distributionally Robust Average-Reward Reinforcement Learning
por: Chen, Zijun, et al.
Publicado: (2025)

Stochastic Zeroth-Order Optimization under Strongly Convexity and Lipschitz Hessian: Minimax Sample Complexity
por: Yu, Qian, et al.
Publicado: (2024)

Geometry, Computation, and Optimality in Stochastic Optimization
por: Cheng, Chen, et al.
Publicado: (2019)

Learning Infinite-Horizon Average-Reward Linear Mixture MDPs of Bounded Span
por: Chae, Woojin, et al.
Publicado: (2024)

On the Robustness of Cross-Concentrated Sampling for Matrix Completion
por: Cai, HanQin, et al.
Publicado: (2024)

Structured Sampling for Robust Euclidean Distance Geometry
por: Kundu, Chandra, et al.
Publicado: (2024)

Minimax-Optimal Reward-Agnostic Exploration in Reinforcement Learning
por: Li, Gen, et al.
Publicado: (2023)

Optimal transport natural gradient for statistical manifolds with continuous sample space
por: Chen, Yifan, et al.
Publicado: (2018)

Finite-Time Minimax Bounds and an Optimal Lyapunov Policy in Queueing Control
por: Liu, Yujie, et al.
Publicado: (2025)

Mixing Time of the Proximal Sampler in Relative Fisher Information via Strong Data Processing Inequality
por: Wibisono, Andre
Publicado: (2025)

Wasserstein Distributionally Robust Estimation in High Dimensions: Performance Analysis and Optimal Hyperparameter Tuning
por: Aolaritei, Liviu, et al.
Publicado: (2022)

Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model
por: Li, Gen, et al.
Publicado: (2020)

Proximal Oracles for Optimization and Sampling
por: Liang, Jiaming, et al.
Publicado: (2024)

Achieving Tractable Minimax Optimal Regret in Average Reward MDPs
por: Boone, Victor, et al.
Publicado: (2024)

The Oracle Complexity of Simplex-based Matrix Games
por: Kornowski, Guy, et al.
Publicado: (2024)

Non-Rectangular Average-Reward Robust MDPs: Optimal Policies and Their Transient Values
por: Wang, Shengbo, et al.
Publicado: (2026)

Fast Computation of Optimal Transport via Entropy-Regularized Extragradient Methods
por: Li, Gen, et al.
Publicado: (2023)

Bellman Optimality of Average-Reward Robust Markov Decision Processes with a Constant Gain
por: Wang, Shengbo, et al.
Publicado: (2025)

Optimal Online Bookmaking for Binary Games
por: Bhatt, Alankrita, et al.
Publicado: (2025)

Linear regression with overparameterized linear neural networks: Tight upper and lower bounds for implicit $\ell^1$-regularization
por: Matt, Hannes, et al.
Publicado: (2025)

A Neural Network Algorithm for KL Divergence Estimation with Quantitative Error Bounds
por: Foss, Mikil, et al.
Publicado: (2025)

A Dual Basis Approach for Structured Robust Euclidean Distance Geometry
por: Kundu, Chandra, et al.
Publicado: (2025)

A Single-Loop First-Order Algorithm for Linearly Constrained Bilevel Optimization
por: Shen, Wei, et al.
Publicado: (2025)

On the Convergence Analysis of Muon
por: Shen, Wei, et al.
Publicado: (2025)

MLorc: Momentum Low-rank Compression for Memory Efficient Large Language Model Adaptation
por: Shen, Wei, et al.
Publicado: (2025)

Convexity in Disguise: A Theoretical Framework for Nonconvex Low-Rank Matrix Estimation
por: Cui, Chengyu, et al.
Publicado: (2026)

Recovering Simultaneously Structured Data via Non-Convex Iteratively Reweighted Least Squares
por: Kümmerle, Christian, et al.
Publicado: (2023)

Generalized Orthogonal Procrustes Problem under Arbitrary Adversaries
por: Ling, Shuyang
Publicado: (2021)

Stochastic Smoothed Gradient Descent Ascent for Federated Minimax Optimization
por: Shen, Wei, et al.
Publicado: (2023)

Tight Regret Bounds for Bayesian Optimization in One Dimension
por: Scarlett, Jonathan
Publicado: (2018)

Variational Inference on the Boolean Hypercube with the Quantum Entropy
por: Beyler, Eliot, et al.
Publicado: (2024)