Provable Benefit of Multitask Representation Learning in Reinforcement Learning

Yuan Cheng, Songtao Feng, Jing Yang, Hong Zhang, Yingbin Liang. Provable Benefit of Multitask Representation Learning in Reinforcement Learning. In Sanmi Koyejo, S. Mohamed, A. Agarwal, Danielle Belgrave, K. Cho, A. Oh, editors, Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, NeurIPS 2022, New Orleans, LA, USA, November 28 - December 9, 2022. 2022. [doi]

@inproceedings{ChengFYZL22,
  title = {Provable Benefit of Multitask Representation Learning in Reinforcement Learning},
  author = {Yuan Cheng and Songtao Feng and Jing Yang and Hong Zhang and Yingbin Liang},
  year = {2022},
  url = {http://papers.nips.cc/paper_files/paper/2022/hash/cde328b7bf6358f5ebb91fe9c539745e-Abstract-Conference.html},
  researchr = {https://researchr.org/publication/ChengFYZL22},
  cites = {0},
  citedby = {0},
  booktitle = {Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, NeurIPS 2022, New Orleans, LA, USA, November 28 - December 9, 2022},
  editor = {Sanmi Koyejo and S. Mohamed and A. Agarwal and Danielle Belgrave and K. Cho and A. Oh},
  isbn = {9781713871088},
}