Robert E. Schapire
- Ecological Modeling top 0.01%
- Artificial Intelligence top 0.01%
- Machine Learning and Algorithms 97
- Machine Learning and Data Classification 31
- Algorithms and Data Compression 27
- Imbalanced Data Classification Techniques 20
- Neural Networks and Applications 14
- Reinforcement Learning in Robotics 12
- Computer Vision and Pattern Recognition top 0.02%
- Nature and Landscape Conservation top 0.1%
- Ecology top 0.05%
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- Advanced Bandit Algorithms Research 37
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- Optimization and Search Problems 17
- Co-authors
- Yoav FreundSteven J. PhillipsRobert P. AndersonYoram SingerMiroslav Dudı́kMary E. BlairPeter L. BartlettNicolò Cesa‐Bianchi
- Journals
- Machine Learning (18 papers)Journal of Machine Learning Research (8 papers)SIAM Journal on Computing (3 papers)
- Partner nations
- United StatesIsraelItaly
In The Last Decade
Robert E. Schapire
155 papers receiving 55.5k citations
Hit Papers
Peers
Comparison fields: 5 of 232
- Ecological Modeling 11.3k
- Artificial Intelligence 24.0k
- Computer Vision and Pattern Recognition 11.8k
- Nature and Landscape Conservation 5.4k
- Ecology 8.5k
Countries citing papers authored by Robert E. Schapire
This map shows the geographic impact of Robert E. Schapire'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 Robert E. Schapire with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Robert E. Schapire more than expected).
Fields of papers citing papers by Robert E. Schapire
This network shows the impact of papers produced by Robert E. Schapire. 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 Robert E. Schapire. The network helps show where Robert E. Schapire may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Robert E. Schapire, 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 | Multiclass Boosting and the Cost of Weak Learning | 2021 | 2 |
| 2 | Robust Inference for Multiclass Classification. | 2018 | 1 |
| 3 | Oracle-Efficient Learning and Auction Design | 2016 | 2 |
| 4 | Collaborative place models | 2015 | 4 |
| 5 | 2013 | 21 | |
| 6 | Non-Stochastic Bandit Slate Problems | 2010 | 32 |
| 7 | The Convergence Rate of AdaBoost. | 2010 | 7 |
| 8 | Margin-based Ranking and an Equivalence between AdaBoost and RankBoost | 2009 | 51 |
| 9 | FilterBoost: Regression and Classification on Large Datasets | 2007 | 50 |
| 10 | Correcting sample selection bias in maximum entropy density estimation | 2005 | 142 |
| 11 | Advances in boosting | 2002 | 4 |
| 12 | Modeling Auction Price Uncertainty Using Boosting-based Conditional Density Estimation | 2002 | 30 |
| 13 | A Generalization of Principal Components Analysis to the Exponential Family | 2001 | 230 |
| 14 | On the Convergence Rate of Good-Turing Estimators | 2000 | 71 |
| 15 | Using output codes to boost multiclass learning problems | 1997 | 157 |
| 16 | Boosting the margin: A new explanation for the effectiveness of voting methods | 1997 | 395 |
| 17 | Proceedings of the tenth annual conference on Computational learning theory | 1997 | 8 |
| 18 | Improving Performance in Neural Networks Using a Boosting Algorithm | 1992 | 101 |
| 19 | 1990 | 4 | |
| 20 | 1990 | 20 |
About Robert E. Schapire
Robert E. Schapire is a scholar working on Artificial Intelligence, Management Science and Operations Research and Ecological Modeling, having authored 160 papers that have together received 59.3k indexed citations. Recurring topics across this work include Machine Learning and Algorithms (97 papers), Advanced Bandit Algorithms Research (37 papers), Machine Learning and Data Classification (31 papers), Algorithms and Data Compression (27 papers), Imbalanced Data Classification Techniques (20 papers), Optimization and Search Problems (17 papers), Neural Networks and Applications (14 papers) and Reinforcement Learning in Robotics (12 papers). The work is most often cited by research in Ecological Modeling (11.3k citations), Artificial Intelligence (24.0k citations) and Computer Vision and Pattern Recognition (11.8k citations). Robert E. Schapire has collaborated with scholars based in United States, Israel and Italy. Frequent co-authors include Yoav Freund, Steven J. Phillips, Robert P. Anderson, Yoram Singer, Miroslav Dudı́k, Mary E. Blair, Peter L. Bartlett, Nicolò Cesa‐Bianchi, Peter Auer and Michael Kearns. Their work appears in journals such as Machine Learning, Journal of Machine Learning Research, SIAM Journal on Computing, Information and Computation and Journal of Computer and System Sciences.
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.