:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autori principali:	Zhang, Yu, Yu, Rui, Yao, Zhipeng, Zhang, Wenyuan, Wang, Jun, Zhang, Liming
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning
Accesso online:	https://arxiv.org/abs/2406.03324
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Corruption-Robust Offline Reinforcement Learning with General Function Approximation
di: Ye, Chenlu, et al.
Pubblicazione: (2023)

Diverse Randomized Value Functions: A Provably Pessimistic Approach for Offline Reinforcement Learning
di: Yu, Xudong, et al.
Pubblicazione: (2024)

Bridging Domain Gaps with Target-Aligned Generation for Offline Reinforcement Learning
di: Kim, Minung, et al.
Pubblicazione: (2026)

VIPO: Value Function Inconsistency Penalized Offline Reinforcement Learning
di: Chen, Xuyang, et al.
Pubblicazione: (2025)

Urban-Focused Multi-Task Offline Reinforcement Learning with Contrastive Data Sharing
di: Zhao, Xinbo, et al.
Pubblicazione: (2024)

Diffusion Policies with Value-Conditional Optimization for Offline Reinforcement Learning
di: Ma, Yunchang, et al.
Pubblicazione: (2025)

Gap-Dependent Bounds for Nearly Minimax Optimal Reinforcement Learning with Linear Function Approximation
di: Zhang, Haochen, et al.
Pubblicazione: (2026)

The Generalization Gap in Offline Reinforcement Learning
di: Mediratta, Ishita, et al.
Pubblicazione: (2023)

OASIS: Conditional Distribution Shaping for Offline Safe Reinforcement Learning
di: Yao, Yihang, et al.
Pubblicazione: (2024)

Value-Guidance MeanFlow for Offline Multi-Agent Reinforcement Learning
di: Pang, Teng, et al.
Pubblicazione: (2026)

Diffusion Policies for Risk-Averse Behavior Modeling in Offline Reinforcement Learning
di: Chen, Xiaocong, et al.
Pubblicazione: (2024)

Bridging Dynamics Gaps via Diffusion Schrödinger Bridge for Cross-Domain Reinforcement Learning
di: Zhang, Hanping, et al.
Pubblicazione: (2026)

Dynamic Momentum Recalibration in Online Gradient Learning
di: Yao, Zhipeng, et al.
Pubblicazione: (2026)

Ensemble Successor Representations for Task Generalization in Offline-to-Online Reinforcement Learning
di: Wang, Changhong, et al.
Pubblicazione: (2024)

Is Value Functions Estimation with Classification Plug-and-play for Offline Reinforcement Learning?
di: Tarasov, Denis, et al.
Pubblicazione: (2024)

Provably Efficient Offline-to-Online Value Adaptation with General Function Approximation
di: Li, Shangzhe, et al.
Pubblicazione: (2026)

Instrumental Variable Value Iteration for Causal Offline Reinforcement Learning
di: Liao, Luofeng, et al.
Pubblicazione: (2021)

Horizon Reduction as Information Loss in Offline Reinforcement Learning
di: Nidadala, Uday Kumar, et al.
Pubblicazione: (2025)

Switching the Loss Reduces the Cost in Batch (Offline) Reinforcement Learning
di: Ayoub, Alex, et al.
Pubblicazione: (2024)

Towards Robust Offline-to-Online Reinforcement Learning via Uncertainty and Smoothness
di: Wen, Xiaoyu, et al.
Pubblicazione: (2023)

Hindsight Preference Learning for Offline Preference-based Reinforcement Learning
di: Gao, Chen-Xiao, et al.
Pubblicazione: (2024)

Federated Offline Reinforcement Learning
di: Zhou, Doudou, et al.
Pubblicazione: (2022)

Policy Constraint by Only Support Constraint for Offline Reinforcement Learning
di: Gao, Yunkai, et al.
Pubblicazione: (2025)

Towards Robust Offline Reinforcement Learning under Diverse Data Corruption
di: Yang, Rui, et al.
Pubblicazione: (2023)

Energy-Weighted Flow Matching for Offline Reinforcement Learning
di: Zhang, Shiyuan, et al.
Pubblicazione: (2025)

Rethinking Optimal Transport in Offline Reinforcement Learning
di: Asadulaev, Arip, et al.
Pubblicazione: (2024)

Offline-to-Online Reinforcement Learning with Classifier-Free Diffusion Generation
di: Huang, Xiao, et al.
Pubblicazione: (2025)

Towards an Information Theoretic Framework of Context-Based Offline Meta-Reinforcement Learning
di: Li, Lanqing, et al.
Pubblicazione: (2024)

Bridging the Gap between Learning and Inference for Diffusion-Based Molecule Generation
di: Liu, Peidong, et al.
Pubblicazione: (2024)

DiM-TS: Bridge the Gap between Selective State Space Models and Time Series for Generative Modeling
di: Yao, Zihao, et al.
Pubblicazione: (2025)

Any-step Dynamics Model Improves Future Predictions for Online and Offline Reinforcement Learning
di: Lin, Haoxin, et al.
Pubblicazione: (2024)

Residuals-based Offline Reinforcement Learning
di: Zhu, Qing, et al.
Pubblicazione: (2026)

Efficient Cross-Domain Offline Reinforcement Learning with Dynamics- and Value-Aligned Data Filtering
di: Qiao, Zhongjian, et al.
Pubblicazione: (2025)

Constrained Policy Optimization with Explicit Behavior Density for Offline Reinforcement Learning
di: Zhang, Jing, et al.
Pubblicazione: (2023)

Energy-Guided Diffusion Sampling for Offline-to-Online Reinforcement Learning
di: Liu, Xu-Hui, et al.
Pubblicazione: (2024)

Augmenting Offline Reinforcement Learning with State-only Interactions
di: Li, Shangzhe, et al.
Pubblicazione: (2024)

Q-value Regularized Decision ConvFormer for Offline Reinforcement Learning
di: Yan, Teng, et al.
Pubblicazione: (2024)

Contrastive Representation for Data Filtering in Cross-Domain Offline Reinforcement Learning
di: Wen, Xiaoyu, et al.
Pubblicazione: (2024)

From Static Constraints to Dynamic Adaptation: Sample-Level Constraint Relaxation for Offline-to-Online Reinforcement Learning
di: Zu, Lipeng, et al.
Pubblicazione: (2025)

Behavior-Regularized Diffusion Policy Optimization for Offline Reinforcement Learning
di: Gao, Chen-Xiao, et al.
Pubblicazione: (2025)