Two papers authored by Dr. Zhu have been accepted for ICLR2025

Two papers authored by Dr. Zhu have been accepted for presentation at the Thirteenth International Conference on Learning Representations, a leading conference in the field of machine learning. The papers introduce innovative methods to advance reinforcement learning.

  • Lingwei Zhu, Han Wang, and Yukie Nagai, “Fat-to-Thin Policy Optimization: Offline Reinforcement Learning with Sparse Policies,” in Proceedings of the Thirteenth International Conference on Learning Representations, April 24-28, 2025.
  • Lingwei Zhu, Haseeb Shah, Han Wang, Yukie Nagai, and Martha White, “q-exponential family for policy optimization,” in Proceedings of the Thirteenth International Conference on Learning Representations, April 24-28, 2025.
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