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Yevgeny Seldin
Yevgeny Seldin
Professor, Department of Computer Science, University of Copenhagen
Verified email at di.ku.dk - Homepage
Title
Cited by
Cited by
Year
Enhanced electronic program guides
M Goldenberg, Y Seldin, A Sterkin
US Patent 8,181,201, 2012
1732012
One practical algorithm for both stochastic and adversarial bandits
Y Seldin, A Slivkins
Proceedings of the 31st International Conference on Machine Learning (ICML …, 2014
1402014
PAC-Bayesian inequalities for martingales
Y Seldin, F Laviolette, N Cesa-Bianchi, J Shawe-Taylor, P Auer
IEEE Transactions on Information Theory 58 (12), 7086-7093, 2012
1032012
An Optimal Algorithm for Stochastic and Adversarial Bandits
J Zimmert, Y Seldin
International Conference on Artificial Intelligence and Statistics (AISTATS), 2019
892019
Online learning in Markov decision processes with adversarially chosen transition probability distributions
Y Abbasi, P Bartlett, V Kanade, Y Seldin, C Szepesvári
Advances in Neural Information Processing Systems, 2508-2516, 2013
85*2013
An Improved Parametrization and Analysis of the EXP3++ Algorithm for Stochastic and Adversarial Bandits
Y Seldin, G Lugosi
Conference on Learning Theory (COLT), 2017
782017
PAC-Bayesian Analysis of Co-clustering and Beyond.
Y Seldin, N Tishby
Journal of Machine Learning Research 11 (12), 2010
782010
Prediction with limited advice and multiarmed bandits with paid observations
Y Seldin, P Bartlett, K Crammer, Y Abbasi-Yadkori
Proceedings of the 31st International Conference on Machine Learning (ICML …, 2014
592014
PAC-Bayes-Empirical-Bernstein Inequality
IO Tolstikhin, Y Seldin
Advances in Neural Information Processing Systems, 109-117, 2013
562013
A Strongly Quasiconvex PAC-Bayesian Bound
N Thiemann, C Igel, O Wingenberger, Y Seldin
Algorithmic Learning Theory (ALT), 2017
532017
PAC-Bayesian analysis of contextual bandits
Y Seldin, P Auer, JS Shawe-Taylor, R Ortner, F Laviolette
Advances in neural information processing systems, 1683-1691, 2011
522011
Tsallis-INF: An Optimal Algorithm for Stochastic and Adversarial Bandits
J Zimmert, Y Seldin
Journal of Machine Learning Research 22 (28), 1-49, 2021
512021
Unsupervised clustering of images using their joint segmentation
Y Seldin, S Starik, M Werman
3rd International Workshop on Statistical and Computational Theories of …, 2003
462003
Evaluation and Analysis of the Performance of the EXP3 Algorithm in Stochastic Environments
Y Seldin, C Szepesvári, P Auer, Y Abbasi-Yadkori
432013
Nonstochastic Multiarmed Bandits with Unrestricted Delays
TS Thune, N Cesa-Bianchi, Y Seldin
Advances in Neural Information Processing Systems (NeurIPS), 2019
382019
Multi-dueling bandits and their application to online ranker evaluation
B Brost, Y Seldin, IJ Cox, C Lioma
Proceedings of the 25th ACM International on Conference on Information and …, 2016
362016
An Optimal Algorithm for Adversarial Bandits with Arbitrary Delays
J Zimmert, Y Seldin
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
342020
Method for content presentation
Y Seldin, A Sterkin
US Patent 8,220,023, 2012
342012
Markovian domain fingerprinting: statistical segmentation of protein sequences
G Bejerano, Y Seldin, H Margalit, N Tishby
Bioinformatics 17 (10), 927-934, 2001
312001
PAC-Bayesian generalization bound for density estimation with application to co-clustering
Y Seldin, N Tishby
International Conference on Artificial Intelligence and Statistics, 472-479, 2009
242009
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