Yevgeny Seldin

Yevgeny Seldin

Professor

ORCID: 0000-0003-3152-4635

Publication year:
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21 - 30 out of 37Page size: 10
  1. 2017
  2. Published

    An improved parametrization and analysis of the EXP3++ algorithm for stochastic and adversarial bandits

    Seldin, Yevgeny & Lugosi, G., 2017, Proceedings of Conference on Learning Theory, 7-10 July 2017, Amsterdam, Netherlands. Kale, S. & Shamir, O. (eds.). Proceedings of Machine Learning Research, p. 1743-1759 (Proceedings of Machine Learning Research, Vol. 65).

    Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

  3. 2018
  4. Published

    Adaptation to Easy Data in Prediction with Limited Advice

    Thune, T. S. & Seldin, Yevgeny, 2018, Proceedings of 32nd Conference on Neural Information Processing Systems (NeurIPS 2018), Montréal, Canada. NIPS Proceedings, 10. (Advances in Neural Information Processing Systems, Vol. 31).

    Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

  5. Published

    Factored Bandits

    Zimmert, J. U. & Seldin, Yevgeny, 2018, Proceedings of 32nd Conference on Neural Information Processing Systems (NeurIPS 2018), Montréal, Canada.. NIPS Proceedings, 10 p. (Advances in Neural Information Processing Systems, Vol. 31).

    Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

  6. 2019
  7. Published

    An Optimal Algorithm for Stochastic and Adversarial Bandits

    Zimmert, J. U. & Seldin, Yevgeny, 2019, Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS). Chaudhuri, K. & Sugiyama, M. (eds.). PMLR, p. 467-475 (Proceedings of Machine Learning Research, Vol. 89).

    Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

  8. Published

    Nonstochastic multiarmed bandits with unrestricted delays

    Thune, T. S., Cesa-Bianchi, N. & Seldin, Yevgeny, 2019, Advances in Neural Information Processing Systems 32 (NeurIPS). NIPS Proceedings, 10 p.

    Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

  9. Published

    On PAC-Bayesian bounds for random forests

    Lorenzen, S. S., Igel, Christian & Seldin, Yevgeny, 2019, In: Machine Learning. 108, 8-9, p. 1503-1522

    Research output: Contribution to journal › Journal article › Research › peer-review

  10. 2020
  11. Published

    An optimal algorithm for adversarial bandits with arbitrary delays

    Zimmert, J. U. & Seldin, Yevgeny, 2020, Proceedings of the 23rdInternational Conference on Artificial Intelligence and Statistics (AISTATS) 2020. PMLR, 9 p. (Proceedings of Machine Learning Research, Vol. 108).

    Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

  12. Published

    Second Order PAC-Bayesian Bounds for the Weighted Majority Vote

    Masegosa, A. R., Lorenzen, S. S., Igel, Christian & Seldin, Yevgeny, 2020, Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual. NeurIPS Proceedings, (Advances in Neural Information Processing Systems, Vol. 33).

    Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

  13. Published

    Tsallis-INF for decoupled exploration and exploitation in multi-armed bandits

    Rouyer, C. & Seldin, Yevgeny, 2020, Proceedings of Thirty Third Conference on Learning Theory(COLT). PMLR, p. 3227-3249 (Proceedings of Machine Learning Research, Vol. 125).

    Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

  14. 2021
  15. Published

    An algorithm for stochastic and adversarial bandits with switching costs

    Rouyer, C., Seldin, Yevgeny & Cesa-Bianchi, N., 2021, Proceedings of the 38th International Conference on Machine Learning (ICML). PMLR, p. 9127-9135 (Proceedings of Machine Learning Research, Vol. 139).

    Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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