Nick Littlestone
Impact in
- Artificial Intelligence top 0.5%
- Machine Learning and Algorithms
- Algorithms and Data Compression
- Machine Learning and Data Classification
- Imbalanced Data Classification Techniques
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- Computability, Logic, AI Algorithms
- Complexity and Algorithms in Graphs
Papers in
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- Machine Learning and Algorithms 16
- Algorithms and Data Compression 9
- Machine Learning and Data Classification 8
- Imbalanced Data Classification Techniques 1
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- Computability, Logic, AI Algorithms 3
- Complexity and Algorithms in Graphs 2
- Co-authors
- Manfred K. Warmuth (4 shared papers)Michael Kearns (2 shared papers)David Haussler (3 shared papers)Dale Schuurmans (2 shared papers)Adam J. Grove (2 shared papers)Claudio Gentile (1 shared paper)Avrim Blum (1 shared paper)Lisa Hellerstein (1 shared paper)
- Journals
- Machine Learning (3 papers)Discrete Applied Mathematics (1 paper)Information and Computation (1 paper)Neural Information Processing Systems (1 paper)Conference on Learning Theory (3 papers)
- Partner nations
- United StatesItaly
In The Last Decade
Nick Littlestone
15 papers receiving 1.6k citations
Nick Littlestone's Hit Papers
Peers
Comparison fields: 5 of 81
- Artificial Intelligence 1.6k
- Computational Theory and Mathematics 413
- Management Science and Operations Research 297
- Computer Networks and Communications 262
- Computer Vision and Pattern Recognition 223
Countries citing papers authored by Nick Littlestone
This map shows the geographic impact of Nick Littlestone'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 Nick Littlestone with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nick Littlestone more than expected).
Fields of papers citing papers by Nick Littlestone
This network shows the impact of papers produced by Nick Littlestone. 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 Nick Littlestone. The network helps show where Nick Littlestone may publish in the future.
Co-authors
The 9 scholars most cited alongside Nick Littlestone, 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 | Learning Quickly When Irrelevant Attributes Abound: A New Linear-Threshold Algorithm Hit paper breakdown → | 1988 | 850 |
| 2 | 1988 | 376 | |
| 3 | 1987 | 96 | |
| 4 | Relating Data Compression and Learnability | 2003 | 86 |
| 5 | 1989 | 83 | |
| 6 | 1991 | 83 | |
| 7 | 2001 | 58 | |
| 8 | 1988 | 53 | |
| 9 | 1997 | 32 | |
| 10 | 1999 | 27 | |
| 11 | An Apobayesian Relative of Winnow | 1996 | 14 |
| 12 | 1991 | 11 | |
| 13 | 1989 | 5 | |
| 14 | Learning Abound: Quickly When Irrelevant Attributes A New Linear-threshold Algorithm | 1988 | 5 |
| 15 | Predicting {0,1}-Functions on Randomly Drawn Points (Extended Abstract) | 1988 | 1 |
| 16 | Learning Quickly When Irrelevant Attributes Abound: A New Linear-threshold Algorithm Extended Abstract | 1987 | 1 |
About Nick Littlestone
Nick Littlestone is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Management Science and Operations Research, Computer Networks and Communications and Infectious Diseases, having authored 16 papers that have together received 1.8k indexed citations. Recurring topics across this work include Machine Learning and Algorithms (16 papers), Algorithms and Data Compression (9 papers), Machine Learning and Data Classification (8 papers), Advanced Bandit Algorithms Research (4 papers), Computability, Logic, AI Algorithms (3 papers), Complexity and Algorithms in Graphs (2 papers), Optimization and Search Problems (2 papers) and Imbalanced Data Classification Techniques (1 paper). The work is most often cited by research in Artificial Intelligence (1.6k citations), Computational Theory and Mathematics (413 citations), Management Science and Operations Research (297 citations), Computer Networks and Communications (262 citations) and Computer Vision and Pattern Recognition (223 citations). Nick Littlestone has collaborated with scholars based in United States and Italy. Frequent co-authors include Manfred K. Warmuth, Michael Kearns, David Haussler, Dale Schuurmans, Adam J. Grove, Claudio Gentile, Avrim Blum, Lisa Hellerstein and Anselm Blumer. Their work appears in journals such as Machine Learning, Discrete Applied Mathematics, Information and Computation, Neural Information Processing Systems 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.