Yevgeny Seldin
Professor
Machine Learning
Universitetsparken 1
2100 København Ø
Online Learning in Markov Decision Processes with Adversarially Chosen Transition Probability Distributions
Abbasi-Yadkori, Y., Bartlett, P. L., Kanade, V., Seldin, Yevgeny & Szepesvári, C., 2013, Advances in Neural Information Processing Systems (NIPS).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Markovian domain fingerprinting: statistical segmentation of protein sequences
Bejerano, G., Seldin, Yevgeny, Tishby, N. & Margalit, H., 2001, In: Bioinformatics.Research output: Contribution to journal › Journal article › Research › peer-review
- Published
An improved multileaving algorithm for online ranker evaluation
Brost, B., Cox, Ingemar Johansson, Seldin, Yevgeny & Lioma, Christina, 2016, Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval: SIGIR '16. Association for Computing Machinery, p. 745-748 4 p.Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Multi-dueling bandits and their application to online ranker evaluation
Brost, B., Seldin, Yevgeny, Cox, Ingemar Johansson & Lioma, Christina, 2016, Proceedings of the 25th ACM International Conference on Information and Knowledge Management. Association for Computing Machinery, p. 2161-2166 6 p. (ACM International Conference on Information and Knowledge Management).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Delayed Bandits: When Do Intermediate Observations Help?
Esposito, E., Masoudian, Saeed, Qiu, H., van der Hoeven, D., Cesa-Bianchi, N. & Seldin, Yevgeny, 2023, Proceedings of the 40 th International Conference on Machine Learnin. PMLR, p. 9374-9395 22 p. (Proceedings of Machine Learning Research, Vol. 202).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
On PAC-Bayesian bounds for random forests
Lorenzen, S. S., Igel, Christian & Seldin, Yevgeny, 2019, In: Machine Learning. 108, 8-9, p. 1503-1522Research output: Contribution to journal › Journal article › Research › peer-review
- 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
- Published
Improved Analysis of the Tsallis-INF Algorithm in Stochastically Constrained Adversarial Bandits and Stochastic Bandits with Adversarial Corruptions
Masoudian, Saeed & Seldin, Yevgeny, Jul 2021, Conference on Learning Theory (COLT 2021). PMLR, p. 3330-3350 (Proceedings of Machine Learning Research, Vol. 134).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
A Best-of-Both-Worlds Algorithm for Bandits with Delayed Feedback
Masoudian, Saeed, Zimmert, J. & Seldin, Yevgeny, 2022, Advances in Neural Information Processing Systems 35 - 36th Conference on Neural Information Processing Systems, NeurIPS 2022. Koyejo, S., Mohamed, S., Agarwal, A., Belgrave, D., Cho, K. & Oh, A. (eds.). NeurIPS Proceedings, 26 p. (Advances in Neural Information Processing Systems, Vol. 35).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
A Near-Optimal Best-of-Both-Worlds Algorithm for Online Learning with Feedback Graphs
Rouyer, C., van der Hoeven, D., Cesa-Bianchi, N. & Seldin, Yevgeny, 2022, Advances in Neural Information Processing Systems 35 (NeurIPS 2022). NeurIPS Proceedings, p. 35035-35048Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
ID: 120818606
Most downloads
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72
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Improved Analysis of the Tsallis-INF Algorithm in Stochastically Constrained Adversarial Bandits and Stochastic Bandits with Adversarial Corruptions
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Published -
30
downloads
Second Order PAC-Bayesian Bounds for the Weighted Majority Vote
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Published -
28
downloads
Tsallis-INF: An optimal algorithm for stochastic and adversarial bandits
Research output: Contribution to journal › Journal article › Research › peer-review
Published