Umar Syed
Impact in
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- Auction Theory and Applications
- Advanced Bandit Algorithms Research
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- Consumer Market Behavior and Pricing
Papers in
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- Machine Learning and Algorithms 9
- Reinforcement Learning in Robotics 4
- Domain Adaptation and Few-Shot Learning 3
- Bayesian Modeling and Causal Inference 3
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- Advanced Bandit Algorithms Research 8
- Auction Theory and Applications 6
- Co-authors
- Golan Yona (2 shared papers)Kareem Amin (5 shared papers)Afshin Rostamizadeh (5 shared papers)Mehryar Mohri (5 shared papers)Robert E. Schapire (3 shared papers)Vitaly Kuznetsov (2 shared papers)Corinna Cortes (2 shared papers)J. D. Williams (1 shared paper)
- Journals
- IEEE Access (1 paper)Lecture notes in computer science (1 paper)Methods in molecular biology (1 paper)SSRN Electronic Journal (1 paper)Neural Information Processing Systems (3 papers)
- Partner nations
- United StatesSwitzerlandSaudi Arabia
In The Last Decade
Umar Syed
24 papers receiving 285 citations
Peers
Comparison fields: 5 of 57
- Management Science and Operations Research 100
- Marketing 41
- Artificial Intelligence 149
- Computer Vision and Pattern Recognition 39
- Computer Networks and Communications 42
Countries citing papers authored by Umar Syed
This map shows the geographic impact of Umar Syed'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 Umar Syed with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Umar Syed more than expected).
Fields of papers citing papers by Umar Syed
This network shows the impact of papers produced by Umar Syed. 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 Umar Syed. The network helps show where Umar Syed may publish in the future.
Co-authors
The 25 scholars most cited alongside Umar Syed, 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 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 38 | |
| 2 | Repeated Contextual Auctions with Strategic Buyers | 2014 | 35 |
| 3 | Deep Boosting | 2014 | 34 |
| 4 | Multi-Class Deep Boosting | 2014 | 34 |
| 5 | 2009 | 31 | |
| 6 | 2003 | 30 | |
| 7 | A Reduction from Apprenticeship Learning to Classification | 2010 | 27 |
| 8 | 2008 | 13 | |
| 9 | Bandits, Query Learning, and the Haystack Dimension | 2011 | 11 |
| 10 | 2025 | 8 | |
| 11 | 2012 | 7 | |
| 12 | 2015 | 7 | |
| 13 | 2017 | 6 | |
| 14 | 2012 | 4 | |
| 15 | 2017 | 4 | |
| 16 | Pricing a low-regret seller | 2016 | 3 |
| 17 | Reinforcement learning without rewards | 2010 | 3 |
| 18 | 2014 | 3 | |
| 19 | 2016 | 3 | |
| 20 | 2024 | 1 |
About Umar Syed
Umar Syed is a scholar working on Artificial Intelligence, Management Science and Operations Research, Computer Networks and Communications, Computer Vision and Pattern Recognition and Information Systems, having authored 26 papers that have together received 306 indexed citations. Recurring topics across this work include Machine Learning and Algorithms (9 papers), Advanced Bandit Algorithms Research (8 papers), Auction Theory and Applications (6 papers), Reinforcement Learning in Robotics (4 papers), Optimization and Search Problems (3 papers), Face and Expression Recognition (3 papers), Domain Adaptation and Few-Shot Learning (3 papers) and Bayesian Modeling and Causal Inference (3 papers). The work is most often cited by research in Management Science and Operations Research (100 citations), Marketing (41 citations), Artificial Intelligence (149 citations), Computer Vision and Pattern Recognition (39 citations) and Computer Networks and Communications (42 citations). Umar Syed has collaborated with scholars based in United States, Switzerland and Saudi Arabia. Frequent co-authors include Golan Yona, Kareem Amin, Afshin Rostamizadeh, Mehryar Mohri, Robert E. Schapire, Vitaly Kuznetsov, Corinna Cortes, J. D. Williams, Michael Kearns and Sergei Vassilvitskii. Their work appears in journals such as IEEE Access, Lecture notes in computer science, Methods in molecular biology, SSRN Electronic Journal and Neural Information Processing Systems.
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.