Provably Efficient Adversarial Imitation Learning with Unknown Transitions. Xu, T., Li, Z., Yu, Y., & Luo, Z. In Evans, R. J. & Shpitser, I., editors, Uncertainty in Artificial Intelligence, UAI 2023, July 31 - 4 August 2023, Pittsburgh, PA, USA, volume 216, of Proceedings of Machine Learning Research, pages 2367–2378, 2023. PMLR. Paper bibtex @inproceedings{DBLP:conf/uai/XuL0L23,
author = {Tian Xu and
Ziniu Li and
Yang Yu and
Zhi{-}Quan Luo},
editor = {Robin J. Evans and
Ilya Shpitser},
title = {Provably Efficient Adversarial Imitation Learning with Unknown Transitions},
booktitle = {Uncertainty in Artificial Intelligence, {UAI} 2023, July 31 - 4 August
2023, Pittsburgh, PA, {USA}},
series = {Proceedings of Machine Learning Research},
volume = {216},
pages = {2367--2378},
publisher = {{PMLR}},
year = {2023},
url = {https://proceedings.mlr.press/v216/xu23c.html},
timestamp = {Mon, 28 Aug 2023 17:23:08 +0200},
biburl = {https://dblp.org/rec/conf/uai/XuL0L23.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
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