:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autori principali:	Corrado, Nicholas E., Hanna, Josiah P.
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning
Accesso online:	https://arxiv.org/abs/2508.01049
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Sparsely Multimodal Data Fusion
di: Bjorgaard, Josiah
Pubblicazione: (2024)

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

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

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

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

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

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

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

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

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

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