Yevgeny Seldin

Orcid: 0000-0003-3152-4635

According to our database1, Yevgeny Seldin authored at least 46 papers between 2001 and 2024.

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Bibliography

2024
Recursive PAC-Bayes: A Frequentist Approach to Sequential Prior Updates with No Information Loss.
CoRR, 2024

2023
An Improved Best-of-both-worlds Algorithm for Bandits with Delayed Feedback.
CoRR, 2023

Delayed Bandits: When Do Intermediate Observations Help?
Proceedings of the International Conference on Machine Learning, 2023

2022
Split-kl and PAC-Bayes-split-kl Inequalities.
CoRR, 2022

A Near-Optimal Best-of-Both-Worlds Algorithm for Online Learning with Feedback Graphs.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

A Best-of-Both-Worlds Algorithm for Bandits with Delayed Feedback.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Split-kl and PAC-Bayes-split-kl Inequalities for Ternary Random Variables.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
Tsallis-INF: An Optimal Algorithm for Stochastic and Adversarial Bandits.
J. Mach. Learn. Res., 2021

Improved Analysis of Robustness of the Tsallis-INF Algorithm to Adversarial Corruptions in Stochastic Multiarmed Bandits.
CoRR, 2021

Chebyshev-Cantelli PAC-Bayes-Bennett Inequality for the Weighted Majority Vote.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

An Algorithm for Stochastic and Adversarial Bandits with Switching Costs.
Proceedings of the 38th International Conference on Machine Learning, 2021

Improved Analysis of the Tsallis-INF Algorithm in Stochastically Constrained Adversarial Bandits and Stochastic Bandits with Adversarial Corruptions.
Proceedings of the Conference on Learning Theory, 2021

2020
Second Order PAC-Bayesian Bounds for the Weighted Majority Vote.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Tsallis-INF for Decoupled Exploration and Exploitation in Multi-armed Bandits.
Proceedings of the Conference on Learning Theory, 2020

An Optimal Algorithm for Adversarial Bandits with Arbitrary Delays.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
On PAC-Bayesian bounds for random forests.
Mach. Learn., 2019

Nonstochastic Multiarmed Bandits with Unrestricted Delays.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

An Optimal Algorithm for Stochastic and Adversarial Bandits.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Factored Bandits.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Adaptation to Easy Data in Prediction with Limited Advice.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017
An Improved Parametrization and Analysis of the EXP3++ Algorithm for Stochastic and Adversarial Bandits.
Proceedings of the 30th Conference on Learning Theory, 2017

A Strongly Quasiconvex PAC-Bayesian Bound.
Proceedings of the International Conference on Algorithmic Learning Theory, 2017

2016
PAC-Bayesian Aggregation without Cross-Validation.
CoRR, 2016

An Improved Multileaving Algorithm for Online Ranker Evaluation.
Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval, 2016

Multi-Dueling Bandits and Their Application to Online Ranker Evaluation.
Proceedings of the 25th ACM International Conference on Information and Knowledge Management, 2016

2014
One Practical Algorithm for Both Stochastic and Adversarial Bandits.
Proceedings of the 31th International Conference on Machine Learning, 2014

Prediction with Limited Advice and Multiarmed Bandits with Paid Observations.
Proceedings of the 31th International Conference on Machine Learning, 2014

2013
Advice-Efficient Prediction with Expert Advice
CoRR, 2013

PAC-Bayes-Empirical-Bernstein Inequality.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Online Learning in Markov Decision Processes with Adversarially Chosen Transition Probability Distributions.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Open Problem: Adversarial Multiarmed Bandits with Limited Advice.
Proceedings of the COLT 2013, 2013

On the Relations and Differences Between Popper Dimension, Exclusion Dimension and VC-Dimension.
Proceedings of the Empirical Inference - Festschrift in Honor of Vladimir N. Vapnik, 2013

2012
PAC-Bayesian Inequalities for Martingales.
IEEE Trans. Inf. Theory, 2012

PAC-Bayes-Bernstein Inequality for Martingales and its Application to Multiarmed Bandits.
Proceedings of the Workshop on On-line Trading of Exploration and Exploitation 2, 2012

Evaluation and Analysis of the Performance of the EXP3 Algorithm in Stochastic Environments.
Proceedings of the Tenth European Workshop on Reinforcement Learning, 2012

2011
PAC-Bayesian Analysis of the Exploration-Exploitation Trade-off
CoRR, 2011

PAC-Bayesian Analysis of Martingales and Multiarmed Bandits
CoRR, 2011

PAC-Bayesian Analysis of Contextual Bandits.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

2010
PAC-Bayesian Analysis of Co-clustering and Beyond.
J. Mach. Learn. Res., 2010

A PAC-Bayesian Analysis of Graph Clustering and Pairwise Clustering
CoRR, 2010

2009
A PAC-Bayesian approach to structure learning (עם תקציר בעברית ושער נוסף: גישה PAC-ביסיאנית ללמידת מבנה.; Probably approximately correct learning.).
PhD thesis, 2009

PAC-Bayesian Generalization Bound for Density Estimation with Application to Co-clustering.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

2008
Multi-classification by categorical features via clustering.
Proceedings of the Machine Learning, 2008

2006
Information Bottleneck for Non Co-Occurrence Data.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

2001
Markovian domain fingerprinting: statistical segmentation of protein sequences.
Bioinform., 2001

Unsupervised Sequence Segmentation by a Mixture of Switching Variable Memory Markov Sources.
Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28, 2001


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