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Jiin Woo

2 accepted papers

2024

Federated Offline Reinforcement Learning: Collaborative Single-Policy Coverage Suffices

ICML 2024poster

Offline reinforcement learning (RL), which seeks to learn an optimal policy using offline data, has garnered significant interest due to its potential in critical applications where online data collection is infeasible or expensive. This work explores the benefit of federated learning for offline RL…

Cited by 11SourcePDFScholar
2023

The Blessing of Heterogeneity in Federated Q-Learning: Linear Speedup and Beyond

ICML 2023poster

In this paper, we consider federated Q-learning, which aims to learn an optimal Q-function by periodically aggregating local Q-estimates trained on local data alone. Focusing on infinite-horizon tabular Markov decision processes, we provide sample complexity guarantees for both the synchronous and a…

Cited by 32SourcePDFScholar