Author

Hang Zhou

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#machine learning Preprint Sep 2026

Provable Benefits of Regularization: Fast Rates for Adversarial Imitation Learning

We study adversarial imitation learning (AIL), in which an agent learns to imitate expert demonstrations by optimizing a policy against an adversarial reward that distinguishes expert and learner behavior. Historically, reward regularization and entropy-based policy regularization are key components of empirically succ...

Hang Zhou, Shang-Zhe Li, А. А. Браверман et al. · 0 citations