Raphaël Féraud
Impact in
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- Advanced Bandit Algorithms Research
- Artificial Intelligence top 10%
- Data Stream Mining Techniques
- Reinforcement Learning in Robotics
- Machine Learning and Algorithms
- Explainable Artificial Intelligence (XAI)
Papers in
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- Reinforcement Learning in Robotics 8
- Data Stream Mining Techniques 7
- Machine Learning and Algorithms 6
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- Advanced Bandit Algorithms Research 16
- Co-authors
- Fabrice Clérot (5 shared papers)Djallel Bouneffouf (7 shared papers)Olivier Bernier (6 shared papers)Michel Collobert (5 shared papers)J.E. Viallet (4 shared papers)Tanguy Urvoy (4 shared papers)Vincent Lemaire (3 shared papers)Odalric-Ambrym Maillard (1 shared paper)
- Journals
- Ad Hoc Networks (1 paper)Neurocomputing (1 paper)Neural Networks (1 paper)Machine Learning (1 paper)Lecture notes in computer science (6 papers)
- Partner nations
- FranceUnited StatesCanada
In The Last Decade
Raphaël Féraud
26 papers receiving 409 citations
Peers
Comparison fields: 5 of 85
- Management Science and Operations Research 147
- Artificial Intelligence 225
- Health Informatics 7
- Computer Vision and Pattern Recognition 113
- Signal Processing 30
Countries citing papers authored by Raphaël Féraud
This map shows the geographic impact of Raphaël Féraud'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 Raphaël Féraud with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Raphaël Féraud more than expected).
Fields of papers citing papers by Raphaël Féraud
This network shows the impact of papers produced by Raphaël Féraud. 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 Raphaël Féraud. The network helps show where Raphaël Féraud may publish in the future.
Co-authors
The 24 scholars most cited alongside Raphaël Féraud, 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 31 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2002 | 122 | |
| 2 | 2002 | 51 | |
| 3 | 2016 | 46 | |
| 4 | 2014 | 35 | |
| 5 | 2014 | 31 | |
| 6 | 2017 | 27 | |
| 7 | 2008 | 24 | |
| 8 | 2015 | 16 | |
| 9 | Random Forest for the Contextual Bandit Problem | 2016 | 13 |
| 10 | 2002 | 12 | |
| 11 | 2002 | 10 | |
| 12 | 1998 | 8 | |
| 13 | Ensemble and Modular Approaches for Face Detection: A Comparison | 1997 | 6 |
| 14 | 2010 | 6 | |
| 15 | A stochastic bandit algorithm for scratch games | 2012 | 4 |
| 16 | 2021 | 4 | |
| 17 | 2023 | 4 | |
| 18 | 2013 | 4 | |
| 19 | 2006 | 4 | |
| 20 | 1997 | 4 |
About Raphaël Féraud
Raphaël Féraud 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 31 papers that have together received 442 indexed citations. Recurring topics across this work include Advanced Bandit Algorithms Research (16 papers), Reinforcement Learning in Robotics (8 papers), Face and Expression Recognition (7 papers), Data Stream Mining Techniques (7 papers), Machine Learning and Algorithms (6 papers), Face recognition and analysis (5 papers), Optimization and Search Problems (3 papers) and Video Surveillance and Tracking Methods (3 papers). The work is most often cited by research in Management Science and Operations Research (147 citations), Artificial Intelligence (225 citations), Health Informatics (7 citations), Computer Vision and Pattern Recognition (113 citations) and Signal Processing (30 citations). Raphaël Féraud has collaborated with scholars based in France, United States and Canada. Frequent co-authors include Fabrice Clérot, Djallel Bouneffouf, Olivier Bernier, Michel Collobert, J.E. Viallet, Tanguy Urvoy, Vincent Lemaire, Odalric-Ambrym Maillard, Romain Laroche and Marc Boullé. Their work appears in journals such as Ad Hoc Networks, Neurocomputing, Neural Networks, Machine Learning and Lecture notes in computer science.
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.