:: Library Catalog

Imagen de Portada

Guardado en:

Detalles Bibliográficos
Autores principales:	Corrado, Nicholas E., Hanna, Josiah P.
Formato:	Preprint
Publicado:	2025
Materias:	Machine Learning
Acceso en línea:	https://arxiv.org/abs/2508.01049
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

On-Policy Policy Gradient Reinforcement Learning Without On-Policy Sampling
por: Corrado, Nicholas E., et al.
Publicado: (2023)

Distributionally Robust Multi-Task Reinforcement Learning via Adaptive Task Sampling
por: Corrado, Nicholas E., et al.
Publicado: (2026)

Understanding when Dynamics-Invariant Data Augmentations Benefit Model-Free Reinforcement Learning Updates
por: Corrado, Nicholas E., et al.
Publicado: (2023)

Guided Data Augmentation for Offline Reinforcement Learning and Imitation Learning
por: Corrado, Nicholas E., et al.
Publicado: (2023)

Demystifying the Paradox of Importance Sampling with an Estimated History-Dependent Behavior Policy in Off-Policy Evaluation
por: Zhou, Hongyi, et al.
Publicado: (2025)

SaVeR: Optimal Data Collection Strategy for Safe Policy Evaluation in Tabular MDP
por: Mukherjee, Subhojyoti, et al.
Publicado: (2024)

Adaptive Exploration for Data-Efficient General Value Function Evaluations
por: Jain, Arushi, et al.
Publicado: (2024)

SPEED: Experimental Design for Policy Evaluation in Linear Heteroscedastic Bandits
por: Mukherjee, Subhojyoti, et al.
Publicado: (2023)

When Can Model-Free Reinforcement Learning be Enough for Thinking?
por: Hanna, Josiah P., et al.
Publicado: (2025)

Pretraining Decision Transformers with Reward Prediction for In-Context Multi-task Structured Bandit Learning
por: Mukherjee, Subhojyoti, et al.
Publicado: (2024)

SMAT: Staged Multi-Agent Training for Co-Adaptive Exoskeleton Control
por: Yuan, Yifei, et al.
Publicado: (2026)

Policy and World Modeling Co-Training for Language Agents
por: Lu, Ning, et al.
Publicado: (2026)

Stable Offline Value Function Learning with Bisimulation-based Representations
por: Pavse, Brahma S., et al.
Publicado: (2024)

Trust the Batch, On- or Off-Policy: Adaptive Policy Optimization for RL Post-Training
por: Fakoor, Rasool, et al.
Publicado: (2026)

Agent-Agnostic Centralized Training for Decentralized Multi-Agent Cooperative Driving
por: Yan, Shengchao, et al.
Publicado: (2024)

Learning to Stabilize Online Reinforcement Learning in Unbounded State Spaces
por: Pavse, Brahma S., et al.
Publicado: (2023)

Adaptive Sample Sharing for Multi Agent Linear Bandits
por: Cherkaoui, Hamza, et al.
Publicado: (2023)

AutoMixAlign: Adaptive Data Mixing for Multi-Task Preference Optimization in LLMs
por: Corrado, Nicholas E., et al.
Publicado: (2025)

An Empirical Study on the Power of Future Prediction in Partially Observable Environments
por: Kwon, Jeongyeol, et al.
Publicado: (2024)

Adaptive Federated LoRA in Heterogeneous Wireless Networks with Independent Sampling
por: Hou, Yanzhao, et al.
Publicado: (2025)

Co2PO: Coordinated Constrained Policy Optimization for Multi-Agent RL
por: Patel, Shrenik, et al.
Publicado: (2026)

MAT-Agent: Adaptive Multi-Agent Training Optimization
por: Zhang, Jusheng, et al.
Publicado: (2025)

Centralized Permutation Equivariant Policy for Cooperative Multi-Agent Reinforcement Learning
por: Xu, Zhuofan, et al.
Publicado: (2025)

Reliable Self-Harm Risk Screening via Adaptive Multi-Agent LLM Systems
por: Karnam, Meghana, et al.
Publicado: (2026)

Reinforcement Learning via Auxiliary Task Distillation
por: Harish, Abhinav Narayan, et al.
Publicado: (2024)

Adaptive Federated Learning in Heterogeneous Wireless Networks with Independent Sampling
por: Geng, Jiaxiang, et al.
Publicado: (2024)

An Introduction to Centralized Training for Decentralized Execution in Cooperative Multi-Agent Reinforcement Learning
por: Amato, Christopher
Publicado: (2024)

Action-Graph Policies: Learning Action Co-dependencies in Multi-Agent Reinforcement Learning
por: Gupta, Nikunj, et al.
Publicado: (2026)

Adaptive Gradient Normalization and Independent Sampling for (Stochastic) Generalized-Smooth Optimization
por: Yang, Yufeng, et al.
Publicado: (2024)

Sparsely Multimodal Data Fusion
por: Bjorgaard, Josiah
Publicado: (2024)

Co-Optimizing Reconfigurable Environments and Policies for Decentralized Multi-Agent Navigation
por: Gao, Zhan, et al.
Publicado: (2024)

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization
por: Liu, Zongkai, et al.
Publicado: (2024)

Rollout-Training Co-Design for Efficient LLM-Based Multi-Agent Reinforcement Learning
por: Jiang, Zhida, et al.
Publicado: (2026)

CoFi-PGMA: Counterfactual Policy Gradients under Filtered Feedback for Multi-Agent LLMs
por: Tong, Stela, et al.
Publicado: (2026)

Decentralized Transformers with Centralized Aggregation are Sample-Efficient Multi-Agent World Models
por: Zhang, Yang, et al.
Publicado: (2024)

Reliability-Aware Adaptive Self-Consistency for Efficient Sampling in LLM Reasoning
por: Kim, Junseok, et al.
Publicado: (2026)

Fully Independent Communication in Multi-Agent Reinforcement Learning
por: Pina, Rafael, et al.
Publicado: (2024)

Emergent Coordination and Phase Structure in Independent Multi-Agent Reinforcement Learning
por: Yamaguchi, Azusa
Publicado: (2025)

Balanced Training of Energy-Based Models with Adaptive Flow Sampling
por: Grenioux, Louis, et al.
Publicado: (2023)

Approximate Global Convergence of Independent Learning in Multi-Agent Systems
por: Jin, Ruiyang, et al.
Publicado: (2024)