Yoav Freund
Impact in
- Artificial Intelligence top 0.01%
- Machine Learning and Algorithms
- Machine Learning and Data Classification
- Imbalanced Data Classification Techniques
- Neural Networks and Applications
- Anomaly Detection Techniques and Applications
- Computer Vision and Pattern Recognition top 0.05%
- Face and Expression Recognition
- Advanced Image and Video Retrieval Techniques
Papers in
-
- Machine Learning and Algorithms 36
- Machine Learning and Data Classification 13
- Algorithms and Data Compression 9
- Neural Networks and Applications 7
- Imbalanced Data Classification Techniques 6
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- Advanced Bandit Algorithms Research 11
- Co-authors
- Robert E. Schapire (26 shared papers)Peter L. Bartlett (2 shared papers)Nicolò Cesa‐Bianchi (6 shared papers)Peter Auer (3 shared papers)Llew Mason (1 shared paper)Eli Shamir (2 shared papers)Naftali Tishby (2 shared papers)H. Sebastian Seung (2 shared papers)
- Journals
- Machine Learning (5 papers)BMC Bioinformatics (3 papers)Information and Computation (3 papers)Journal of Computer and System Sciences (2 papers)The Annals of Statistics (2 papers)
- Partner nations
- United StatesIsraelItaly
In The Last Decade
Yoav Freund
88 papers receiving 29.1k citations
Yoav Freund's Hit Papers
Peers
Comparison fields: 5 of 229
- Artificial Intelligence 15.7k
- Computer Vision and Pattern Recognition 8.2k
- Management Science and Operations Research 3.0k
- Signal Processing 2.3k
- Information Systems 2.9k
Countries citing papers authored by Yoav Freund
This map shows the geographic impact of Yoav Freund'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 Yoav Freund with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yoav Freund more than expected).
Fields of papers citing papers by Yoav Freund
This network shows the impact of papers produced by Yoav Freund. 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 Yoav Freund. The network helps show where Yoav Freund may publish in the future.
Co-authors
The 25 scholars most cited alongside Yoav Freund, 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 90 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting Hit paper breakdown → | 1997 | 12974 |
| 2 | Experiments with a new boosting algorithm Hit paper breakdown → | 1996 | 5032 |
| 3 | A Short Introduction to Boosting Hit paper breakdown → | 1999 | 1950 |
| 4 | Boosting the margin: a new explanation for the effectiveness of voting methods Hit paper breakdown → | 1998 | 1537 |
| 5 | Boosting a Weak Learning Algorithm by Majority Hit paper breakdown → | 1995 | 1092 |
| 6 | The Nonstochastic Multiarmed Bandit Problem Hit paper breakdown → | 2002 | 1092 |
| 7 | Selective Sampling Using the Query by Committee Algorithm Hit paper breakdown → | 1997 | 744 |
| 8 | Large margin classification using the perceptron algorithm Hit paper breakdown → | 1998 | 740 |
| 9 | An Efficient Boosting Algorithm for Combining Preferences Hit paper breakdown → | 1998 | 643 |
| 10 | The Alternating Decision Tree Learning Algorithm Hit paper breakdown → | 1999 | 512 |
| 11 | Experiment with a new boosting algorithm | 1996 | 406 |
| 12 | 2007 | 405 | |
| 13 | 1999 | 399 | |
| 14 | Boosting the margin: A new explanation for the effectiveness of voting methods | 1997 | 395 |
| 15 | 1997 | 349 | |
| 16 | 2012 | 272 | |
| 17 | 1999 | 271 | |
| 18 | 1996 | 228 | |
| 19 | 2008 | 202 | |
| 20 | Unsupervised learning of distributions on binary vectors using two layer networks | 1991 | 174 |
About Yoav Freund
Yoav Freund is a scholar working on Artificial Intelligence, Management Science and Operations Research, Computer Vision and Pattern Recognition, Computational Theory and Mathematics and Computer Networks and Communications, having authored 90 papers that have together received 31.3k indexed citations. Recurring topics across this work include Machine Learning and Algorithms (36 papers), Machine Learning and Data Classification (13 papers), Advanced Bandit Algorithms Research (11 papers), Algorithms and Data Compression (9 papers), Optimization and Search Problems (8 papers), Face and Expression Recognition (8 papers), Neural Networks and Applications (7 papers) and Imbalanced Data Classification Techniques (6 papers). The work is most often cited by research in Artificial Intelligence (15.7k citations), Computer Vision and Pattern Recognition (8.2k citations), Management Science and Operations Research (3.0k citations), Signal Processing (2.3k citations) and Information Systems (2.9k citations). Yoav Freund has collaborated with scholars based in United States, Israel and Italy. Frequent co-authors include Robert E. Schapire, Peter L. Bartlett, Nicolò Cesa‐Bianchi, Peter Auer, Llew Mason, Eli Shamir, Naftali Tishby, H. Sebastian Seung, Yoram Singer and David Haussler. Their work appears in journals such as Machine Learning, BMC Bioinformatics, Information and Computation, Journal of Computer and System Sciences and The Annals of Statistics.
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.