Ofer Dekel
Impact in
- Artificial Intelligence top 0.5%
- Machine Learning and Algorithms
- Topic Modeling
- Natural Language Processing Techniques
- Data Stream Mining Techniques
- Machine Learning and Data Classification
- Text and Document Classification Technologies
- Stochastic Gradient Optimization Techniques
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- Advanced Bandit Algorithms Research
Papers in
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- Advanced Bandit Algorithms Research 17
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- Machine Learning and Algorithms 27
- Text and Document Classification Technologies 8
- Machine Learning and Data Classification 7
- Imbalanced Data Classification Techniques 7
- Data Stream Mining Techniques 4
- Reinforcement Learning in Robotics 4
- Co-authors
- Yoram SingerShai Shalev‐ShwartzJoseph KeshetOhad ShamirKoby CrammerLin XiaoRan Gilad-BachrachAlekh Agarwal
- Journals
- Journal of Machine Learning Research (3 papers)Journal of Computer and System Sciences (1 paper)Machine Learning (1 paper)SIAM Journal on Computing (1 paper)IEEE Transactions on Information Theory (1 paper)
- Partner nations
- United StatesIsraelUnited Kingdom
In The Last Decade
Ofer Dekel
40 papers receiving 2.5k citations
Hit Papers
Peers
Comparison fields: 5 of 110
- Artificial Intelligence 2.1k
- Management Science and Operations Research 541
- Computer Science Applications 167
- Computer Vision and Pattern Recognition 577
- Signal Processing 201
Countries citing papers authored by Ofer Dekel
This map shows the geographic impact of Ofer Dekel'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 Ofer Dekel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ofer Dekel more than expected).
Fields of papers citing papers by Ofer Dekel
This network shows the impact of papers produced by Ofer Dekel. 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 Ofer Dekel. The network helps show where Ofer Dekel may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ofer Dekel, 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 | Online Learning with a Hint | 2017 | 3 |
| 2 | Adaptive Neural Networks for Fast Test-Time Prediction. | 2017 | 21 |
| 3 | Bandit smooth convex optimization: improving the bias-variance tradeoff | 2015 | 5 |
| 4 | Better Rates for Any Adversarial Deterministic MDP | 2013 | 7 |
| 5 | Selective sampling and active learning from single and multiple teachers | 2012 | 38 |
| 6 | There’s a Hole in My Data Space: Piecewise Predictors for Heterogeneous Learning Problems | 2012 | 6 |
| 7 | Optimal Distributed Online Prediction | 2011 | 39 |
| 8 | Multiclass-Multilabel Classification with More Classes than Examples. | 2010 | 35 |
| 9 | Optimal Algorithms for Online Convex Optimization with Multi-Point Bandit Feedback. | 2010 | 121 |
| 10 | Robust Selective Sampling from Single and Multiple Teachers. | 2010 | 27 |
| 11 | Vox Populi: Collecting High-Quality Labels from a Crowd | 2009 | 93 |
| 12 | Distribution-Calibrated Hierarchical Classification | 2009 | 2 |
| 13 | From Online to Batch Learning with Cutoff-Averaging | 2008 | 14 |
| 14 | 2007 | 31 | |
| 15 | A Boosting Algorithm for Label Covering in Multilabel Problems | 2007 | 10 |
| 16 | Data-Driven Online to Batch Conversions | 2005 | 19 |
| 17 | The Power of Selective Memory: Self-Bounded Learning of Prediction Suffix Trees | 2004 | 11 |
| 18 | Online Passive-Aggressive Algorithms | 2003 | 54 |
| 19 | Log-Linear Models for Label Ranking | 2003 | 99 |
| 20 | Multiclass Learning by Probabilistic Embeddings | 2002 | 24 |
About Ofer Dekel
Ofer Dekel is a scholar working on Management Science and Operations Research, Artificial Intelligence, Computer Networks and Communications, Safety Research and Computer Vision and Pattern Recognition, having authored 40 papers that have together received 2.7k indexed citations. Recurring topics across this work include Machine Learning and Algorithms (27 papers), Advanced Bandit Algorithms Research (17 papers), Optimization and Search Problems (8 papers), Text and Document Classification Technologies (8 papers), Machine Learning and Data Classification (7 papers), Imbalanced Data Classification Techniques (7 papers), Data Stream Mining Techniques (4 papers) and Reinforcement Learning in Robotics (4 papers). The work is most often cited by research in Artificial Intelligence (2.1k citations), Management Science and Operations Research (541 citations), Computer Science Applications (167 citations), Computer Vision and Pattern Recognition (577 citations) and Signal Processing (201 citations). Ofer Dekel has collaborated with scholars based in United States, Israel and United Kingdom. Frequent co-authors include Yoram Singer, Shai Shalev‐Shwartz, Joseph Keshet, Ohad Shamir, Koby Crammer, Lin Xiao, Ran Gilad-Bachrach, Alekh Agarwal, Christopher D. Manning and Felix Fischer. Their work appears in journals such as Journal of Machine Learning Research, Journal of Computer and System Sciences, Machine Learning, SIAM Journal on Computing and IEEE Transactions on Information 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.