Sparse-Reg: Improving Sample Complexity in Offline Reinforcement Learning using Sparsity
Fuente:
arXiv
Saved in:
| Main Authors: | Arnob, Samin Yeasar, Fujimoto, Scott, Precup, Doina |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Partial Models for Building Adaptive Model-Based Reinforcement Learning Agents
by: Alver, Safa, et al.
Published: (2024)
by: Alver, Safa, et al.
Published: (2024)
Parseval Regularization for Continual Reinforcement Learning
by: Chung, Wesley, et al.
Published: (2024)
by: Chung, Wesley, et al.
Published: (2024)
Exploring Sparse Adapters for Scalable Merging of Parameter Efficient Experts
by: Arnob, Samin Yeasar, et al.
Published: (2025)
by: Arnob, Samin Yeasar, et al.
Published: (2025)
Fluid-Agent Reinforcement Learning
by: Sharma, Shishir, et al.
Published: (2026)
by: Sharma, Shishir, et al.
Published: (2026)
Diversity-Enriched Option-Critic
by: Kamat, Anand, et al.
Published: (2020)
by: Kamat, Anand, et al.
Published: (2020)
Functional Acceleration for Policy Mirror Descent
by: Chelu, Veronica, et al.
Published: (2024)
by: Chelu, Veronica, et al.
Published: (2024)
A Look at Value-Based Decision-Time vs. Background Planning Methods Across Different Settings
by: Alver, Safa, et al.
Published: (2022)
by: Alver, Safa, et al.
Published: (2022)
Incorporating Spatial Information into Goal-Conditioned Hierarchical Reinforcement Learning via Graph Representations
by: Zhang, Shuyuan, et al.
Published: (2025)
by: Zhang, Shuyuan, et al.
Published: (2025)
Reinforcement Learning with Pairwise Preferences in Long-Term Decision Problems
by: Carr, Jonathan Colaço, et al.
Published: (2026)
by: Carr, Jonathan Colaço, et al.
Published: (2026)
More Efficient Randomized Exploration for Reinforcement Learning via Approximate Sampling
by: Ishfaq, Haque, et al.
Published: (2024)
by: Ishfaq, Haque, et al.
Published: (2024)
Understanding Behavioral Metric Learning: A Large-Scale Study on Distracting Reinforcement Learning Environments
by: Luo, Ziyan, et al.
Published: (2025)
by: Luo, Ziyan, et al.
Published: (2025)
Consciousness-Inspired Spatio-Temporal Abstractions for Better Generalization in Reinforcement Learning
by: Zhao, Mingde, et al.
Published: (2023)
by: Zhao, Mingde, et al.
Published: (2023)
Adaptive Exploration for Data-Efficient General Value Function Evaluations
by: Jain, Arushi, et al.
Published: (2024)
by: Jain, Arushi, et al.
Published: (2024)
Sparsity-based Safety Conservatism for Constrained Offline Reinforcement Learning
by: Cho, Minjae, et al.
Published: (2024)
by: Cho, Minjae, et al.
Published: (2024)
Reinforcement Learning With Sparse-Executing Actions via Sparsity Regularization
by: Pang, Jing-Cheng, et al.
Published: (2021)
by: Pang, Jing-Cheng, et al.
Published: (2021)
Fairness in Reinforcement Learning with Bisimulation Metrics
by: Rezaei-Shoshtari, Sahand, et al.
Published: (2024)
by: Rezaei-Shoshtari, Sahand, et al.
Published: (2024)
Sample Efficient Active Algorithms for Offline Reinforcement Learning
by: Roy, Soumyadeep, et al.
Published: (2026)
by: Roy, Soumyadeep, et al.
Published: (2026)
Capacity-Constrained Continual Learning
by: Wen, Zheng, et al.
Published: (2025)
by: Wen, Zheng, et al.
Published: (2025)
Policy Gradient Methods in the Presence of Symmetries and State Abstractions
by: Panangaden, Prakash, et al.
Published: (2023)
by: Panangaden, Prakash, et al.
Published: (2023)
On Sample-Efficient Offline Reinforcement Learning: Data Diversity, Posterior Sampling, and Beyond
by: Nguyen-Tang, Thanh, et al.
Published: (2024)
by: Nguyen-Tang, Thanh, et al.
Published: (2024)
Diffusion-DICE: In-Sample Diffusion Guidance for Offline Reinforcement Learning
by: Mao, Liyuan, et al.
Published: (2024)
by: Mao, Liyuan, et al.
Published: (2024)
When is Offline Policy Selection Sample Efficient for Reinforcement Learning?
by: Liu, Vincent, et al.
Published: (2023)
by: Liu, Vincent, et al.
Published: (2023)
Improving Offline Reinforcement Learning with Inaccurate Simulators
by: Hou, Yiwen, et al.
Published: (2024)
by: Hou, Yiwen, et al.
Published: (2024)
Finite time analysis of temporal difference learning with linear function approximation: Tail averaging and regularisation
by: Patil, Gandharv, et al.
Published: (2022)
by: Patil, Gandharv, et al.
Published: (2022)
On the Statistical Complexity for Offline and Low-Adaptive Reinforcement Learning with Structures
by: Yin, Ming, et al.
Published: (2025)
by: Yin, Ming, et al.
Published: (2025)
Uncovering a Universal Abstract Algorithm for Modular Addition in Neural Networks
by: McCracken, Gavin, et al.
Published: (2025)
by: McCracken, Gavin, et al.
Published: (2025)
LEASE: Offline Preference-based Reinforcement Learning with High Sample Efficiency
by: Liu, Xiao-Yin, et al.
Published: (2024)
by: Liu, Xiao-Yin, et al.
Published: (2024)
Offline Trajectory Optimization for Offline Reinforcement Learning
by: Zhao, Ziqi, et al.
Published: (2024)
by: Zhao, Ziqi, et al.
Published: (2024)
On the Complexity of Offline Reinforcement Learning with $Q^\star$-Approximation and Partial Coverage
by: Liu, Haolin, et al.
Published: (2026)
by: Liu, Haolin, et al.
Published: (2026)
Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization
by: Liu, Zongkai, et al.
Published: (2024)
by: Liu, Zongkai, et al.
Published: (2024)
Rotation-Preserving Supervised Fine-Tuning
by: Jin, Hangzhan, et al.
Published: (2026)
by: Jin, Hangzhan, et al.
Published: (2026)
ENOTO: Improving Offline-to-Online Reinforcement Learning with Q-Ensembles
by: Zhao, Kai, et al.
Published: (2023)
by: Zhao, Kai, et al.
Published: (2023)
Improving Offline-to-Online Reinforcement Learning with Q Conditioned State Entropy Exploration
by: Zhang, Ziqi, et al.
Published: (2023)
by: Zhang, Ziqi, et al.
Published: (2023)
Towards General-Purpose Model-Free Reinforcement Learning
by: Fujimoto, Scott, et al.
Published: (2025)
by: Fujimoto, Scott, et al.
Published: (2025)
Offline Multitask Representation Learning for Reinforcement Learning
by: Ishfaq, Haque, et al.
Published: (2024)
by: Ishfaq, Haque, et al.
Published: (2024)
On The Sample Complexity Bounds In Bilevel Reinforcement Learning
by: Gaur, Mudit, et al.
Published: (2025)
by: Gaur, Mudit, et al.
Published: (2025)
SMORE: Score Models for Offline Goal-Conditioned Reinforcement Learning
by: Sikchi, Harshit, et al.
Published: (2023)
by: Sikchi, Harshit, et al.
Published: (2023)
Improving Decision Sparsity
by: Sun, Yiyang, et al.
Published: (2024)
by: Sun, Yiyang, et al.
Published: (2024)
Preference Elicitation for Offline Reinforcement Learning
by: Pace, Alizée, et al.
Published: (2024)
by: Pace, Alizée, et al.
Published: (2024)
Offline Reinforcement Learning with Imbalanced Datasets
by: Jiang, Li, et al.
Published: (2023)
by: Jiang, Li, et al.
Published: (2023)
Similar Items
-
Partial Models for Building Adaptive Model-Based Reinforcement Learning Agents
by: Alver, Safa, et al.
Published: (2024) -
Parseval Regularization for Continual Reinforcement Learning
by: Chung, Wesley, et al.
Published: (2024) -
Exploring Sparse Adapters for Scalable Merging of Parameter Efficient Experts
by: Arnob, Samin Yeasar, et al.
Published: (2025) -
Fluid-Agent Reinforcement Learning
by: Sharma, Shishir, et al.
Published: (2026) -
Diversity-Enriched Option-Critic
by: Kamat, Anand, et al.
Published: (2020)