:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autori principali:	Fan, Junyi, Han, Yuxuan, Zeng, Jialin, Cai, Jian-Feng, Wang, Yang, Xiang, Yang, Zhang, Jiheng
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning
Accesso online:	https://arxiv.org/abs/2403.11544
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Refined Sample Complexity for Markov Games with Independent Linear Function Approximation
di: Dai, Yan, et al.
Pubblicazione: (2024)

Improving Sample Efficiency of Model-Free Algorithms for Zero-Sum Markov Games
di: Feng, Songtao, et al.
Pubblicazione: (2023)

Distributionally Robust Online Markov Game with Linear Function Approximation
di: Zheng, Zewu, et al.
Pubblicazione: (2025)

Improved Generalization Bounds for Transductive Learning by Transductive Local Complexity and Its Applications
di: Yang, Yingzhen
Pubblicazione: (2023)

Efficient Transfer Learning via Causal Bounds
di: Gong, Xueping, et al.
Pubblicazione: (2023)

Independent and Decentralized Learning in Markov Potential Games
di: Maheshwari, Chinmay, et al.
Pubblicazione: (2022)

Independent Learning in Constrained Markov Potential Games
di: Jordan, Philip, et al.
Pubblicazione: (2024)

Independent Learning in Performative Markov Potential Games
di: Sahitaj, Rilind, et al.
Pubblicazione: (2025)

Improved Amenability Bounds for Local Coordination Games
di: Peretz, Ron, et al.
Pubblicazione: (2026)

On the Existence of Sum‐Of‐Squares Lyapunov Functions for Polynomial Parameter‐Varying Systems With Locally Exponential Stability
di: Jialin Chen, et al.
Pubblicazione: (2025)

An Evolutionary Game With the Game Transitions Based on the Markov Process
di: Feng, Minyu, et al.
Pubblicazione: (2025)

Approximation of Functions: Optimal Sampling and Complexity
di: Krieg, David, et al.
Pubblicazione: (2026)

Approximate State Abstraction for Markov Games
di: Ishibashi, Hiroki, et al.
Pubblicazione: (2024)

Finite-Sample Analysis of Nonlinear Independent Component Analysis:Sample Complexity and Identifiability Bounds
di: Jiang, Yuwen
Pubblicazione: (2026)

Locally Repairable Convertible Codes: Improved Lower Bound and General Construction
di: Ge, Songping, et al.
Pubblicazione: (2025)

Reinforcement Learning from Partial Observation: Linear Function Approximation with Provable Sample Efficiency
di: Cai, Qi, et al.
Pubblicazione: (2022)

Incentivize without Bonus: Provably Efficient Model-based Online Multi-agent RL for Markov Games
di: Yang, Tong, et al.
Pubblicazione: (2025)

Identification and Adaptive Control of Markov Jump Systems: Sample Complexity and Regret Bounds
di: Sattar, Yahya, et al.
Pubblicazione: (2021)

Sample-efficient Learning of Infinite-horizon Average-reward MDPs with General Function Approximation
di: He, Jianliang, et al.
Pubblicazione: (2024)

Value Function Decomposition in Markov Recommendation Process
di: Wang, Xiaobei, et al.
Pubblicazione: (2025)

Improved Sample Complexity Bounds for Diffusion Model Training
di: Gupta, Shivam, et al.
Pubblicazione: (2023)

Space-Bounded Communication Complexity of Unitaries
di: Li, Longcheng, et al.
Pubblicazione: (2025)

Primal-Dual Sample Complexity Bounds for Constrained Markov Decision Processes with Multiple Constraints
di: Buckley, Max, et al.
Pubblicazione: (2025)

Backward-Friendly Optimization: Training Large Language Models with Approximate Gradients under Memory Constraints
di: Yang, Jing, et al.
Pubblicazione: (2025)

New and Improved Bounds for Markov Paging
di: Pabbaraju, Chirag, et al.
Pubblicazione: (2025)

Practical Global and Local Bounds in Gaussian Process Regression via Chaining
di: Liu, Junyi, et al.
Pubblicazione: (2025)

Metric Entropy-Free Sample Complexity Bounds for Sample Average Approximation in Convex Stochastic Programming
di: Liu, Hongcheng, et al.
Pubblicazione: (2024)

Misspecified $Q$-Learning with Sparse Linear Function Approximation: Tight Bounds on Approximation Error
di: Du, Ally Yalei, et al.
Pubblicazione: (2024)

Achieving Optimal Sample Complexity for a Broader Class of Signals in Sparse Phase Retrieval
di: Xu, Mengchu, et al.
Pubblicazione: (2025)

VI-CuRL: Stabilizing Verifier-Independent RL Reasoning via Confidence-Guided Variance Reduction
di: Cai, Xin-Qiang, et al.
Pubblicazione: (2026)

Improving Reinforcement Learning Sample-Efficiency using Local Approximation
di: Prashant, Mohit, et al.
Pubblicazione: (2025)

Near-Optimal Policy Optimization for Correlated Equilibrium in General-Sum Markov Games
di: Cai, Yang, et al.
Pubblicazione: (2024)

Design of a Linearity Improved Hybrid Asymmetric Load Modulated Balanced Amplifier
di: Benhao Jin, et al.
Pubblicazione: (2026)

Sample Complexity Bounds for Estimating Probability Divergences under Invariances
di: Tahmasebi, Behrooz, et al.
Pubblicazione: (2023)

Arena-Independent Memory Bounds for Nash Equilibria in Reachability Games
di: Main, James C. A.
Pubblicazione: (2023)

Taming the Curses of Multiagency in Robust Markov Games with Large State Space through Linear Function Approximation
di: Gai, Jingchu, et al.
Pubblicazione: (2026)

FlowPortal: Residual-Corrected Flow for Training-Free Video Relighting and Background Replacement
di: Gao, Wenshuo, et al.
Pubblicazione: (2025)

Thompson Sampling in Online RLHF with General Function Approximation
di: Feng, Songtao, et al.
Pubblicazione: (2025)

Tight Sampling Bounds for Eigenvalue Approximation
di: Swartworth, William, et al.
Pubblicazione: (2024)

Tackling Heavy-Tailed Rewards in Reinforcement Learning with Function Approximation: Minimax Optimal and Instance-Dependent Regret Bounds
di: Huang, Jiayi, et al.
Pubblicazione: (2023)