Research output per year
Research output per year
Personal profile
Short presentation
I am working in the area of <b>Machine Learning</b> with primary focus on <b>Online Learning</b> and <b>PAC-Bayesian analysis</b>. For more information, please, check <b><a href="https://sites.google.com/site/yevgenyseldin/">https://sites.google.com/site/yevgenyseldin/</a></b>
Fingerprint
Dive into the research topics where Yevgeny Seldin is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
- 4 Similar Profiles
-
An Optimal Algorithm for Stochastic and Adversarial Bandits
Zimmert, J. U. & Seldin, Y., 2019, Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS). Proceedings of Machine Learning ResearchResearch output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
-
On PAC-Bayesian bounds for random forests
Lorenzen, S. S., Igel, C. & Seldin, Y., 15 Sept 2019, In: Machine Learning. 108, 8-9, p. 1503-1522Research output: Contribution to journal › Journal article › Research › peer-review
-
Adaptation to Easy Data in Prediction with Limited Advice
Thune, T. S. & Seldin, Y., 2018, Advances in Neural Information Processing Systems (NeurIPS).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
1 Citation (Scopus) -
Factored Bandits
Zimmert, J. U. & Seldin, Y., 2018, Advances in Neural Information Processing Systems (NeurIPS).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
-
An improved parametrization and analysis of the EXP3++ algorithm for stochastic and adversarial bandits
Seldin, Y. & 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
-
A strongly quasiconvex PAC-Bayesian bound
Thiemann, N., Igel, C., Wintenberger, O. & Seldin, Y., 2017, Proceedings of International Conference on Algorithmic Learning Theory, 15-17 October 2017, Kyoto University, Kyoto, Japan . Hanneke, S. & Reyzin, L. (eds.). Proceedings of Machine Learning Research, p. 466-492 (Proceedings of Machine Learning Research, Vol. 76).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
-
An improved multileaving algorithm for online ranker evaluation
Brost, B., Cox, I. J., Seldin, Y. & Lioma, C., 7 Jul 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
-
Multi-dueling bandits and their application to online ranker evaluation
Brost, B., Seldin, Y., Cox, I. J. & Lioma, C., 24 Oct 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