Yevgeny Seldin

808 total citations
30 papers, 266 citations indexed

About

Yevgeny Seldin is a scholar working on Artificial Intelligence, Management Science and Operations Research and Computer Vision and Pattern Recognition. According to data from OpenAlex, Yevgeny Seldin has authored 30 papers receiving a total of 266 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Artificial Intelligence, 17 papers in Management Science and Operations Research and 4 papers in Computer Vision and Pattern Recognition. Recurrent topics in Yevgeny Seldin's work include Advanced Bandit Algorithms Research (17 papers), Machine Learning and Algorithms (15 papers) and Reinforcement Learning in Robotics (7 papers). Yevgeny Seldin is often cited by papers focused on Advanced Bandit Algorithms Research (17 papers), Machine Learning and Algorithms (15 papers) and Reinforcement Learning in Robotics (7 papers). Yevgeny Seldin collaborates with scholars based in Germany, United States and Israel. Yevgeny Seldin's co-authors include Naftali Tishby, Peter Auer, Aleksandrs Slivkins, John Shawe‐Taylor, Peter L. Bartlett, Nicolò Cesa‐Bianchi, Yasin Abbasi-Yadkori, Ilya Tolstikhin, Csaba Szepesvári and François Laviolette and has published in prestigious journals such as Bioinformatics, IEEE Transactions on Information Theory and Journal of Machine Learning Research.

In The Last Decade

Yevgeny Seldin

27 papers receiving 255 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Yevgeny Seldin Germany 10 215 126 41 30 25 30 266
Javier G. Marı́n-Blázquez Spain 10 192 0.9× 76 0.6× 63 1.5× 10 0.3× 12 0.5× 20 292
Kush Bhatia United States 6 279 1.3× 26 0.2× 15 0.4× 8 0.3× 78 3.1× 12 341
Alicia P. Wolfe United States 5 138 0.6× 27 0.2× 91 2.2× 11 0.4× 10 0.4× 6 244
Dmitry Pechyony United States 9 175 0.8× 18 0.1× 12 0.3× 6 0.2× 101 4.0× 12 222
Shweta Jain India 8 67 0.3× 90 0.7× 55 1.3× 35 1.2× 23 0.9× 28 200
Mukund Narasimhan United States 10 159 0.7× 17 0.1× 36 0.9× 13 0.4× 84 3.4× 14 272
Yiwei Wang Singapore 7 203 0.9× 11 0.1× 13 0.3× 10 0.3× 46 1.8× 14 262
Srinivas Vadrevu United States 9 202 0.9× 22 0.2× 46 1.1× 7 0.2× 55 2.2× 17 287
Radu Marinescu Ireland 8 199 0.9× 37 0.3× 128 3.1× 7 0.2× 25 1.0× 45 279
Carlos Domingo Japan 6 189 0.9× 11 0.1× 16 0.4× 12 0.4× 58 2.3× 12 250

Countries citing papers authored by Yevgeny Seldin

Since Specialization
Citations

This map shows the geographic impact of Yevgeny Seldin's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Yevgeny Seldin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yevgeny Seldin more than expected).

Fields of papers citing papers by Yevgeny Seldin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yevgeny Seldin. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Yevgeny Seldin. The network helps show where Yevgeny Seldin may publish in the future.

Co-authorship network of co-authors of Yevgeny Seldin

This figure shows the co-authorship network connecting the top 25 collaborators of Yevgeny Seldin. A scholar is included among the top collaborators of Yevgeny Seldin based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yevgeny Seldin. Yevgeny Seldin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Seldin, Yevgeny, et al.. (2019). An Optimal Algorithm for Adversarial Bandits with Arbitrary Delays. Research at the University of Copenhagen (University of Copenhagen). 3285–3294. 1 indexed citations
2.
Seldin, Yevgeny, et al.. (2018). An Optimal Algorithm for Stochastic and Adversarial Bandits. Research at the University of Copenhagen (University of Copenhagen). 467–475. 7 indexed citations
3.
Seldin, Yevgeny, et al.. (2018). Factored Bandits. Neural Information Processing Systems. 31. 2840–2849. 1 indexed citations
4.
Seldin, Yevgeny, et al.. (2018). Adaptation to Easy Data in Prediction with Limited Advice. arXiv (Cornell University). 31. 2909–2918. 1 indexed citations
5.
Seldin, Yevgeny & Gábor Lugosi. (2017). An Improved Parametrization and Analysis of the EXP3++ Algorithm for Stochastic and Adversarial Bandits. Research at the University of Copenhagen (University of Copenhagen). 8 indexed citations
6.
Seldin, Yevgeny, Peter L. Bartlett, Koby Crammer, & Yasin Abbasi-Yadkori. (2014). Prediction with Limited Advice and Multiarmed Bandits with Paid Observations. QUT ePrints (Queensland University of Technology). 280–287. 19 indexed citations
7.
Seldin, Yevgeny & Aleksandrs Slivkins. (2014). One Practical Algorithm for Both Stochastic and Adversarial Bandits. QUT ePrints (Queensland University of Technology). 1287–1295. 27 indexed citations
8.
Tolstikhin, Ilya & Yevgeny Seldin. (2013). PAC-Bayes-empirical-Bernstein inequality. QUT ePrints (Queensland University of Technology). 15 indexed citations
9.
Seldin, Yevgeny, Csaba Szepesvári, Peter Auer, & Yasin Abbasi-Yadkori. (2013). Evaluation and Analysis of the Performance of the EXP3 Algorithm in Stochastic Environments. Max Planck Digital Library. 103–116. 17 indexed citations
10.
Seldin, Yevgeny, Koby Crammer, & Peter L. Bartlett. (2013). Open Problem: Adversarial Multiarmed Bandits with Limited Advice. QUT ePrints (Queensland University of Technology). 1067–1072. 1 indexed citations
11.
Bartlett, Peter L., et al.. (2013). Online Learning in Markov Decision Processes with Adversarially Chosen Transition Probability Distributions. arXiv (Cornell University). 26. 2508–2516. 19 indexed citations
12.
Seldin, Yevgeny, Peter Auer, John Shawe‐Taylor, Ronald Ortner, & François Laviolette. (2011). PAC-Bayesian Analysis of Contextual Bandits. MPG.PuRe (Max Planck Society). 24. 1683–1691. 19 indexed citations
13.
Seldin, Yevgeny, François Laviolette, Nicolò Cesa‐Bianchi, John Shawe‐Taylor, & Peter Auer. (2011). PAC-Bayesian Inequalities for Martingales. arXiv (Cornell University). 12–12. 1 indexed citations
14.
Seldin, Yevgeny & Naftali Tishby. (2010). PAC-Bayesian Analysis of Co-clustering and Beyond. Journal of Machine Learning Research. 11(117). 3595–3646. 36 indexed citations
15.
Seldin, Yevgeny. (2010). A PAC-Bayesian Analysis of Co-clustering, Graph Clustering, and Pairwise Clustering. MPG.PuRe (Max Planck Society). 1–5. 1 indexed citations
16.
Seldin, Yevgeny & Naftali Tishby. (2009). PAC-Bayesian Generalization Bound for Density Estimation with Application to Co-clustering. MPG.PuRe (Max Planck Society). 472–479. 8 indexed citations
17.
Bejerano, Gill, et al.. (2001). Extraction of Protein Domains and Signatures through Unsupervised Statistical Sequence Segmentation.
18.
Seldin, Yevgeny, Gill Bejerano, & Naftali Tishby. (2001). Unsupervised Segmentation and Classification of Mixtures of Markovian Sources. MPG.PuRe (Max Planck Society). 1–15. 1 indexed citations
19.
Seldin, Yevgeny, Gill Bejerano, & Naftali Tishby. (2001). Unsupervised Sequence Segmentation by a Mixture of Switching Variable Memory Markov Sources. MPG.PuRe (Max Planck Society). 513–520. 9 indexed citations
20.
Bejerano, Gill, Yevgeny Seldin, Hanah Margalit, & Naftali Tishby. (2001). Markovian domain fingerprinting: statistical segmentation of protein sequences. Bioinformatics. 17(10). 927–934. 8 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact

Rankless by CCL
2026