Non-Stochastic Multi-Player Multi-Armed Bandits: Optimal Rate With Collision Information, Sublinear Without

Sébastien Bubeck, Yuanzhi Li, Yuval Peres, Mark Sellke. Non-Stochastic Multi-Player Multi-Armed Bandits: Optimal Rate With Collision Information, Sublinear Without. In Jacob D. Abernethy, Shivani Agarwal 0001, editors, Conference on Learning Theory, COLT 2020, 9-12 July 2020, Virtual Event [Graz, Austria]. Volume 125 of Proceedings of Machine Learning Research, pages 961-987, PMLR, 2020. [doi]

@inproceedings{BubeckLPS20,
  title = {Non-Stochastic Multi-Player Multi-Armed Bandits: Optimal Rate With Collision Information, Sublinear Without},
  author = {Sébastien Bubeck and Yuanzhi Li and Yuval Peres and Mark Sellke},
  year = {2020},
  url = {http://proceedings.mlr.press/v125/bubeck20c.html},
  researchr = {https://researchr.org/publication/BubeckLPS20},
  cites = {0},
  citedby = {0},
  pages = {961-987},
  booktitle = {Conference on Learning Theory, COLT 2020, 9-12 July 2020, Virtual Event [Graz, Austria]},
  editor = {Jacob D. Abernethy and Shivani Agarwal 0001},
  volume = {125},
  series = {Proceedings of Machine Learning Research},
  publisher = {PMLR},
}