Provable Benefits of Regularization: Fast Rates for Adversarial Imitation Learning
Dually Regularized AIL is the first algorithm to simultaneously achieve $\widetilde{O}\left(\frac{1}{\epsilon}\right)$ sample complexity in both expert demonstrations and online interactions for this regularized AIL objective, even with stochastic experts.
Hang Zhou, Shang-Zhe Li, А. А. Браверман et al.
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