Yevgeny Seldin
Professor
Machine Learning
Universitetsparken 1
2100 København Ø
- 2001
- 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
Unsupervised sequence segmentation by a mixture of variable memory length Markov sources
Seldin, Yevgeny, Bejerano, G. & Tishby, N., 2001, Proceedings of the 18th International Conference on Machine Learning (ICML).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- 2003
- Published
Unsupervised segmentation and classification of mixtures of Markovian sources
Seldin, Yevgeny, Starik, S. & Werman, M., 2003.Research output: Contribution to conference › Paper › Research › peer-review
- 2007
- Published
Information bottleneck for non co-occurrence data
Seldin, Yevgeny, Slonim, N. & Tishby, N., 2007, Advances in Neural Information Processing Systems (NIPS).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- 2008
- Published
Multi-classification by categorical features via clustering
Seldin, Yevgeny & Tishby, N., 2008, Proceedings of the 25th International Conference on Machine Learning (ICML).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- 2009
- Published
PAC-Bayesian generalization bound for density estimation with application to co-clustering
Seldin, Yevgeny & Tishby, N., 2009, JMLR Workshop and Conference Proceedings, 5 (AISTATS).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- 2010
PAC-Bayesian analysis of co-clustering and beyond
Seldin, Yevgeny & Tishby, N., 2010, In: Journal of Machine Learning Research. 11, p. 3595-3646 52 p.Research output: Contribution to journal › Journal article › Research › peer-review
- 2011
PAC-Bayesian analysis of contextual bandits
Seldin, Yevgeny, Auer, P., Laviolette, F., Shawe-Taylor, J. & Ortner, R., 2011, Advances in Neural Information Processing Systems (NIPS).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- 2012
PAC-Bayes-Bernstein inequality for martingales and its application to multiarmed bandits
Seldin, Yevgeny, Cesa-Bianchi, N., Auer, P., Laviolette, F. & Shawe-Taylor, J., 2012, JMLR Workshop and Conference Proceedings, 26.Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
PAC-Bayesian inequalities for martingales
Seldin, Yevgeny, Laviolette, F., Cesa-Bianchi, N., Shawe-Taylor, J. & Auer, P., 2012, In: I E E E Transactions on Information Theory. 58, 12Research output: Contribution to journal › Journal article › Research › peer-review
- 2013
Evaluation and analysis of the performance of the EXP3 algorithm in stochastic environments
Seldin, Yevgeny, Szepesvári, C., Auer, P. & Abbasi-Yadkori, Y., 2013, JMLR Workshop and Conference Proceedings, 24 (EWRL).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
On the Relations and Differences between Popper Dimension, Exclusion Dimension and VC-Dimension
Seldin, Yevgeny & Schölkopf, B., 2013, Festschrift in Honor of Vladimir N. Vapnik. SpringerResearch output: Chapter in Book/Report/Conference proceeding › Book chapter › Research › peer-review
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
Open problem: Adversarial multiarmed bandits with limited advice
Seldin, Yevgeny, Crammer, K. & Bartlett, P. L., 2013, JMLR Workshop and Conference Proceedings, 30 (COLT).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
PAC-Bayes-Empirical-Bernstein Inequality
Tolstikhin, I. & Seldin, Yevgeny, 2013, Advances in Neural Information Processing Systems (NIPS).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- 2014
One practical algorithm for both stochastic and adversarial bandits
Seldin, Yevgeny & Slivkins, A., 2014, JMLR Workshop and Conference Proceedings, 32 (ICML).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Prediction with limited advice and multiarmed bandits with paid observations
Seldin, Yevgeny, Bartlett, P. L., Crammer, K. & Abbasi-Yadkori, Y., 2014, JMLR Workshop and Conference Proceedings, 32 (ICML).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- 2016
- 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
- 2017
- Published
A strongly quasiconvex PAC-Bayesian bound
Thiemann, N., Igel, Christian, Wintenberger, O. & Seldin, Yevgeny, 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
- 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
- 2018
- 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
- 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
- 2019
- 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
- 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
ID: 120818606
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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
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Second Order PAC-Bayesian Bounds for the Weighted Majority Vote
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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28
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Tsallis-INF: An optimal algorithm for stochastic and adversarial bandits
Research output: Contribution to journal › Journal article › Research › peer-review
Published