Koby Crammer
Impact in
- Artificial Intelligence top 0.05%
- Domain Adaptation and Few-Shot Learning
- Topic Modeling
- Natural Language Processing Techniques
- Machine Learning and Algorithms
- Text and Document Classification Technologies
- Machine Learning and ELM
-
- Face and Expression Recognition
- Multimodal Machine Learning Applications
Papers in
-
- Machine Learning and Algorithms 45
- Machine Learning and Data Classification 23
- Text and Document Classification Technologies 17
- Topic Modeling 13
- Data Stream Mining Techniques 13
- Domain Adaptation and Few-Shot Learning 12
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- Advanced Bandit Algorithms Research 28
- Co-authors
- Yoram Singer (16 shared papers)Fernando Pereira (14 shared papers)John Blitzer (3 shared papers)Shai Ben-David (2 shared papers)Alex Kulesza (7 shared papers)Jennifer Wortman Vaughan (2 shared papers)Mark Dredze (12 shared papers)Joseph Keshet (2 shared papers)
- Journals
- Machine Learning (6 papers)Journal of Machine Learning Research (3 papers)PLoS Computational Biology (2 papers)Bioinformatics (1 paper)Proceedings of the VLDB Endowment (1 paper)
- Partner nations
- IsraelUnited StatesCanada
In The Last Decade
Koby Crammer
109 papers receiving 10.6k citations
Koby Crammer's Hit Papers
Peers
Comparison fields: 5 of 180
- Artificial Intelligence 8.5k
- Computer Vision and Pattern Recognition 3.6k
- Signal Processing 766
- Management Science and Operations Research 762
- Information Systems 972
Countries citing papers authored by Koby Crammer
This map shows the geographic impact of Koby Crammer'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 Koby Crammer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Koby Crammer more than expected).
Fields of papers citing papers by Koby Crammer
This network shows the impact of papers produced by Koby Crammer. 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 Koby Crammer. The network helps show where Koby Crammer may publish in the future.
Co-authors
The 25 scholars most cited alongside Koby Crammer, 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 110 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | A theory of learning from different domains Hit paper breakdown → | 2009 | 2199 |
| 2 | On the algorithmic implementation of multiclass kernel-based vector machines Hit paper breakdown → | 2002 | 1342 |
| 3 | Analysis of Representations for Domain Adaptation Hit paper breakdown → | 2007 | 1333 |
| 4 | Online Passive-Aggressive Algorithms Hit paper breakdown → | 2006 | 1126 |
| 5 | Online large-margin training of dependency parsers Hit paper breakdown → | 2005 | 612 |
| 6 | On the Learnability and Design of Output Codes for Multiclass Problems Hit paper breakdown → | 2002 | 518 |
| 7 | 2002 | 413 | |
| 8 | 2008 | 294 | |
| 9 | Learning Bounds for Domain Adaptation | 2007 | 241 |
| 10 | 2013 | 228 | |
| 11 | 2001 | 178 | |
| 12 | Margin Analysis of the LVQ Algorithm | 2002 | 160 |
| 13 | A family of additive online algorithms for category ranking | 2003 | 145 |
| 14 | 2009 | 137 | |
| 15 | Breaking the curse of kernelization: budgeted stochastic gradient descent for large-scale SVM training | 2012 | 133 |
| 16 | Robust support vector machine training via convex outlier ablation | 2006 | 117 |
| 17 | Kernel Design Using Boosting | 2002 | 105 |
| 18 | Online Classification on a Budget | 2003 | 102 |
| 19 | Exact Convex Confidence-Weighted Learning | 2008 | 100 |
| 20 | 2016 | 99 |
About Koby Crammer
Koby Crammer is a scholar working on Artificial Intelligence, Management Science and Operations Research, Computer Vision and Pattern Recognition, Computer Networks and Communications and Signal Processing, having authored 110 papers that have together received 11.3k indexed citations. Recurring topics across this work include Machine Learning and Algorithms (45 papers), Advanced Bandit Algorithms Research (28 papers), Machine Learning and Data Classification (23 papers), Text and Document Classification Technologies (17 papers), Topic Modeling (13 papers), Data Stream Mining Techniques (13 papers), Face and Expression Recognition (12 papers) and Domain Adaptation and Few-Shot Learning (12 papers). The work is most often cited by research in Artificial Intelligence (8.5k citations), Computer Vision and Pattern Recognition (3.6k citations), Signal Processing (766 citations), Management Science and Operations Research (762 citations) and Information Systems (972 citations). Koby Crammer has collaborated with scholars based in Israel, United States and Canada. Frequent co-authors include Yoram Singer, Fernando Pereira, John Blitzer, Shai Ben-David, Alex Kulesza, Jennifer Wortman Vaughan, Mark Dredze, Joseph Keshet, Ofer Dekel and Shai Shalev‐Shwartz. Their work appears in journals such as Machine Learning, Journal of Machine Learning Research, PLoS Computational Biology, Bioinformatics and Proceedings of the VLDB Endowment.
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.