Lev Reyzin
Impact in
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- Advanced Bandit Algorithms Research
Papers in
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- Machine Learning and Algorithms 18
- Machine Learning and Data Classification 8
- Algorithms and Data Compression 4
- Imbalanced Data Classification Techniques 4
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- Complexity and Algorithms in Graphs 9
- Co-authors
- Robert E. Schapire (4 shared papers)Lihong Li (1 shared paper)Wei Chu (1 shared paper)Vitaly Feldman (3 shared papers)Ying Xiao (3 shared papers)Elena Grigorescu (3 shared papers)Santosh Vempala (3 shared papers)Satyen Kale (1 shared paper)
- Journals
- Theoretical Computer Science (2 papers)Journal of the ACM (1 paper)Journal of Machine Learning Research (1 paper)Nature (1 paper)Journal of Complex Networks (1 paper)
- Partner nations
- United States
In The Last Decade
Lev Reyzin
28 papers receiving 566 citations
Peers
Comparison fields: 5 of 79
- Management Science and Operations Research 258
- Computational Mathematics 8
- Artificial Intelligence 380
- Computer Networks and Communications 118
- Computer Vision and Pattern Recognition 92
Countries citing papers authored by Lev Reyzin
This map shows the geographic impact of Lev Reyzin'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 Lev Reyzin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lev Reyzin more than expected).
Fields of papers citing papers by Lev Reyzin
This network shows the impact of papers produced by Lev Reyzin. 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 Lev Reyzin. The network helps show where Lev Reyzin may publish in the future.
Co-authors
The 25 scholars most cited alongside Lev Reyzin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Contextual bandits with linear Payoff functions | 2011 | 244 |
| 2 | 2006 | 149 | |
| 3 | 2013 | 38 | |
| 4 | 2017 | 33 | |
| 5 | Non-Stochastic Bandit Slate Problems | 2010 | 32 |
| 6 | Boosting on a Budget: Sampling for Feature-Efficient Prediction | 2011 | 12 |
| 7 | 2019 | 9 | |
| 8 | 2006 | 8 | |
| 9 | 2013 | 7 | |
| 10 | 2014 | 7 | |
| 11 | 2017 | 7 | |
| 12 | 2015 | 7 | |
| 13 | 2017 | 7 | |
| 14 | 2019 | 6 | |
| 15 | An Optimal High Probability Algorithm for the Contextual Bandit Problem | 2010 | 5 |
| 16 | Statistical Algorithms and a Lower Bound for Planted Clique | 2012 | 4 |
| 17 | Proceedings of the 28th International Conference on Algorithmic Learning Theory | 2017 | 4 |
| 18 | 2017 | 3 | |
| 19 | 2008 | 2 | |
| 20 | 2019 | 2 |
About Lev Reyzin
Lev Reyzin is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Computer Networks and Communications, Management Science and Operations Research and Computer Vision and Pattern Recognition, having authored 30 papers that have together received 596 indexed citations. Recurring topics across this work include Machine Learning and Algorithms (18 papers), Complexity and Algorithms in Graphs (9 papers), Machine Learning and Data Classification (8 papers), Optimization and Search Problems (6 papers), Algorithms and Data Compression (4 papers), Imbalanced Data Classification Techniques (4 papers), Advanced Bandit Algorithms Research (3 papers) and Facility Location and Emergency Management (2 papers). The work is most often cited by research in Management Science and Operations Research (258 citations), Computational Mathematics (8 citations), Artificial Intelligence (380 citations), Computer Networks and Communications (118 citations) and Computer Vision and Pattern Recognition (92 citations). Lev Reyzin has collaborated with scholars based in United States. Frequent co-authors include Robert E. Schapire, Lihong Li, Wei Chu, Vitaly Feldman, Ying Xiao, Elena Grigorescu, Santosh Vempala, Satyen Kale, Shalev Ben-David and Nikhil Srivastava. Their work appears in journals such as Theoretical Computer Science, Journal of the ACM, Journal of Machine Learning Research, Nature and Journal of Complex Networks.
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.