Yevgeny Seldin

Yevgeny Seldin

Associate Professor


  1. 2019
  2. Published

    An Optimal Algorithm for Stochastic and Adversarial Bandits. / Zimmert, Julian Ulf; Seldin, Yevgeny.

    Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS). Proceedings of Machine Learning Research, 2019.

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

  3. Published

    On PAC-Bayesian bounds for random forests. / Lorenzen, Stephan S.; Igel, Christian; Seldin, Yevgeny.

    In: Machine Learning, Vol. 108, No. 8-9, 2019, p. 1503-1522.

    Research output: Contribution to journalJournal articleResearchpeer-review

  4. 2018
  5. Published

    Adaptation to Easy Data in Prediction with Limited Advice. / Thune, Tobias Sommer; Seldin, Yevgeny.

    Advances in Neural Information Processing Systems (NeurIPS). 2018.

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

  6. Published

    Factored Bandits. / Zimmert, Julian Ulf; Seldin, Yevgeny.

    Advances in Neural Information Processing Systems (NeurIPS). 2018.

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

  7. 2017
  8. Published

    A strongly quasiconvex PAC-Bayesian bound. / Thiemann, Niklas; Igel, Christian; Wintenberger, Olivier; Seldin, Yevgeny.

    Proceedings of International Conference on Algorithmic Learning Theory, 15-17 October 2017, Kyoto University, Kyoto, Japan . ed. / Steve Hanneke; Lev Reyzin. Proceedings of Machine Learning Research, 2017. p. 466-492 (Proceedings of Machine Learning Research, Vol. 76).

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

  9. Published

    An improved parametrization and analysis of the EXP3++ algorithm for stochastic and adversarial bandits. / Seldin, Yevgeny; Lugosi, Gábor.

    Proceedings of Conference on Learning Theory, 7-10 July 2017, Amsterdam, Netherlands. ed. / Satyen Kale; Ohad Shamir . Proceedings of Machine Learning Research, 2017. p. 1743-1759 (Proceedings of Machine Learning Research, Vol. 65).

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

  10. 2016
  11. Published

    An improved multileaving algorithm for online ranker evaluation. / Brost, Brian; Cox, Ingemar Johansson; Seldin, Yevgeny; Lioma, Christina.

    Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval: SIGIR '16. Association for Computing Machinery, 2016. p. 745-748.

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

  12. Published

    Multi-dueling bandits and their application to online ranker evaluation. / Brost, Brian; Seldin, Yevgeny; Cox, Ingemar Johansson; Lioma, Christina.

    Proceedings of the 25th ACM International Conference on Information and Knowledge Management. Association for Computing Machinery, 2016. p. 2161-2166 (ACM International Conference on Information and Knowledge Management).

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

  13. 2014
  14. One practical algorithm for both stochastic and adversarial bandits. / Seldin, Yevgeny; Slivkins, Aleksandrs.

    JMLR Workshop and Conference Proceedings, 32 (ICML). 2014.

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

  15. Prediction with limited advice and multiarmed bandits with paid observations. / Seldin, Yevgeny; Bartlett, Peter L.; Crammer, Koby; Abbasi-Yadkori, Yasin.

    JMLR Workshop and Conference Proceedings, 32 (ICML). 2014.

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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