Dávid Pál
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- Advanced Bandit Algorithms Research 9
- Artificial Intelligence top 2%
- Machine Learning and Algorithms 6
- Bayesian Methods and Mixture Models 2
- Data Stream Mining Techniques 2
- Reinforcement Learning in Robotics 2
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- Optimization and Search Problems 7
- Marketing top 10%
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- graph theory and CDMA systems 2
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- Advanced Graph Theory Research 2
- Co-authors
- Csaba SzepesváriYasin Abbasi-YadkoriTyler LuShai Ben-DavidMartin PálBarnabás PóczosGagan AggarwalS. Muthukrishnan
- Cited by
- Management Science and Operations ResearchArtificial IntelligenceComputer Networks and Communications
- Journals
- Theoretical Computer Science (1 paper)Mathematics of Operations Research (1 paper)Graphs and Combinatorics (1 paper)
- Partner nations
- CanadaUnited StatesSlovakia
In The Last Decade
Dávid Pál
18 papers receiving 746 citations
Hit Papers
Peers
Comparison fields: 5 of 60
- Management Science and Operations Research 499
- Artificial Intelligence 494
- Computer Networks and Communications 173
- Marketing 68
- Computer Vision and Pattern Recognition 92
Countries citing papers authored by Dávid Pál
This map shows the geographic impact of Dávid Pál'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 Dávid Pál with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dávid Pál more than expected).
Fields of papers citing papers by Dávid Pál
This network shows the impact of papers produced by Dávid Pál. 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 Dávid Pál. The network helps show where Dávid Pál may publish in the future.
Co-authorship network
The 21 scholars most cited alongside Dávid Pál, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 2 | |
| 2 | 2018 | 1 | |
| 3 | Hardness of Online Sleeping Combinatorial Optimization Problems | 2016 | 3 |
| 4 | Open Problem: Parameter-Free and Scale-Free Online Algorithms | 2016 | 1 |
| 5 | 2014 | 32 | |
| 6 | Online-to-Confidence-Set Conversions and Application to Sparse Stochastic Bandits | 2012 | 26 |
| 7 | 2012 | 8 | |
| 8 | Improved Algorithms for Linear Stochastic Banditsbreakdown → | 2011 | 314 |
| 9 | Minimax Regret of Finite Partial-Monitoring Games in Stochastic Environments | 2011 | 13 |
| 10 | Contextual Multi-Armed Bandits | 2010 | 90 |
| 11 | Impossibility Theorems for Domain Adaptation | 2010 | 87 |
| 12 | 2010 | 54 | |
| 13 | Agnostic Online Learning. | 2009 | 36 |
| 14 | 2009 | 58 | |
| 15 | Does Unlabeled Data Provably Help? Worst-case Analysis of the Sample Complexity of Semi-Supervised Learning. | 2008 | 52 |
| 16 | 2008 | 7 | |
| 17 | 2007 | 5 | |
| 18 | 2007 | 1 |
About Dávid Pál
Dávid Pál is a scholar working on Management Science and Operations Research, Artificial Intelligence, Computer Networks and Communications, Computational Theory and Mathematics and Statistics and Probability, having authored 18 papers that have together received 790 indexed citations. Recurring topics across this work include Advanced Bandit Algorithms Research (9 papers), Optimization and Search Problems (7 papers), Machine Learning and Algorithms (6 papers), graph theory and CDMA systems (2 papers), Advanced Graph Theory Research (2 papers), Bayesian Methods and Mixture Models (2 papers), Data Stream Mining Techniques (2 papers) and Reinforcement Learning in Robotics (2 papers). The work is most often cited by research in Management Science and Operations Research (499 citations), Artificial Intelligence (494 citations), Computer Networks and Communications (173 citations), Marketing (68 citations) and Computer Vision and Pattern Recognition (92 citations). Dávid Pál has collaborated with scholars based in Canada, United States and Slovakia. Frequent co-authors include Csaba Szepesvári, Yasin Abbasi-Yadkori, Tyler Lu, Shai Ben-David, Martin Pál, Barnabás Póczos, Gagan Aggarwal, S. Muthukrishnan, Gábor Bartók and Shai Shalev‐Shwartz. Their work appears in journals such as Theoretical Computer Science, Mathematics of Operations Research, Graphs and Combinatorics, Electronic Notes in Discrete Mathematics and Conference on Learning Theory.
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.