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cs.LG2022★ 1 cited
Minimax Regret Optimization for Robust Machine Learning under Distribution Shift
Alekh Agarwal, Tong Zhang
In this paper, we consider learning scenarios where the learned model is evaluated under an unknown test distribution which potentially differs from the training distribution (i.e.…
cs.LG2022★ 3 cited
Pessimistic Minimax Value Iteration: Provably Efficient Equilibrium Learning from Offline Datasets
Han Zhong, Wei Xiong, Jiyuan Tan +4
We study episodic two-player zero-sum Markov games (MGs) in the offline setting, where the goal is to find an approximate Nash equilibrium (NE) policy pair based on a dataset colle…