Michèle Sébag
- Artificial Intelligence top 1%
- Computational Theory and Mathematics top 1%
- Information Systems top 2%
- Computer Networks and Communications top 5%
- Signal Processing top 5%
- Co-authors
- Marc SchoenauerÁlvaro FialhoAlexandre TermierIlya LoshchilovXiangliang ZhangCécile Germain‐RenaudLuís Da CostaCyril Furtlehner
- Topics
- Metaheuristic Optimization Algorithms Research (20 papers)Evolutionary Algorithms and Applications (16 papers)Machine Learning and Algorithms (12 papers)
- Partner nations
- FranceUnited KingdomChina
In The Last Decade
Michèle Sébag
82 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 118
- Artificial Intelligence 1.0k
- Computational Theory and Mathematics 461
- Information Systems 333
- Computer Networks and Communications 323
- Signal Processing 191
Countries citing papers authored by Michèle Sébag
This map shows the geographic impact of Michèle Sébag'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 Michèle Sébag with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michèle Sébag more than expected).
Fields of papers citing papers by Michèle Sébag
This network shows the impact of papers produced by Michèle Sébag. 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 Michèle Sébag. The network helps show where Michèle Sébag may publish in the future.
Co-authorship network of co-authors of Michèle Sébag
This figure shows the co-authorship network connecting the top 25 collaborators of Michèle Sébag. A scholar is included among the top collaborators of Michèle Sébag based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Michèle Sébag. Michèle Sébag is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 17 | |
| 2 | 38 | |
| 3 | A brief Review of the ChaLearn AutoML Challenge: Any-time Any-dataset Learning without Human Intervention | 28 |
| 4 | Programming by Feedback | 15 |
| 5 | 1 | |
| 6 | SpikeAnts, a spiking neuron network modelling the emergence of organization in a complex system | 4 |
| 7 | Feature Selection as a One-Player Game | 34 |
| 8 | 5 | |
| 9 | Frugal and Online Affinity Propagation | 2 |
| 10 | 79 | |
| 11 | A machine learning approach for statistical software testing | 17 |
| 12 | EXIST: Exploitation/Exploration Inference for Statistical Software Testing | 0 |
| 13 | A multi-objective multi-modal optimization approach for mining stable spatio-temporal patterns | 18 |
| 14 | 1 | |
| 15 | Relational learning as search in a critical region | 15 |
| 16 | Constraint-based Learning of Long Relational Concepts | 3 |
| 17 | 24 | |
| 18 | Combining statistics and semantics for word and document clustering | 10 |
| 19 | Toward Civilized Evolution: Developing Inhibitions. | 14 |
| 20 | Delaying the Choice of Bias: A Disjunctive Version Space Approach | 3 |
About Michèle Sébag
Michèle Sébag is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Management Science and Operations Research, having authored 86 papers that have together received 1.7k indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (20 papers), Evolutionary Algorithms and Applications (16 papers) and Machine Learning and Algorithms (12 papers). The work is most often cited by research in Artificial Intelligence (1.0k citations), Computational Theory and Mathematics (461 citations) and Health Informatics (27 citations). Michèle Sébag has collaborated with scholars based in France, United Kingdom and China. Frequent co-authors include Marc Schoenauer, Álvaro Fialho, Alexandre Termier, Ilya Loshchilov, Xiangliang Zhang, Cécile Germain‐Renaud, Luís Da Costa, Cyril Furtlehner, Olivier Teytaud and David López-Paz. Their work appears in journals such as Bioinformatics, Communications of the ACM and Artificial Intelligence.
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.