University Jean Monnet, St-Etienne
Hubert Curien Lab. UMR CNRS 5516
Data Intelligence group
Address:18 rue du Prof. Benoît Lauras
42000 Saint-Etienne, France
Office: F020a
Email: marc.sebban[AT]univ-st-etienne.fr
Tel: (+33)(0)477915865
Some representative papers
- ICML'2025: A Bregman Proximal Viewpoint on Neural Operators
- ECML'2025: Provably accurate adaptive sampling for collocation points in physics-informed neural networks
- ECML'2024: Approximation Error of Sobolev Regular Functions with tanh Neural Networks: Theoretical Impact on PINNs
- Physical Review Letters'2023: Learning complexity to guide light-induced self-organized nanopatterns
- AAAI'2022: Optimal Tensor Transport
- Machine Learning Journal (2021): Sampled Gromov Wasserstein
- April 2020: A survey on domain adaptation theory
- ICML'2020: A Swiss Army Knife for Minimax Optimal Transport
- IJCAI'2020: Metric Learning in Optimal Transport for Domain Adaptation
- IJCAI'2020: Learning from Few Positives: a Provably Accurate Metric Learning Algorithm to Deal with Imbalanced Data
- AISTATS'2019: From Cost-Sensitive Classification to Tight F-measure Bounds
- IJCAI'2019: Differentially Private Optimal Transport: Application to Domain Adaptation
- ECML'2017: Theoretical Analysis of Domain Adaptation with Optimal Transport.
- NeurIPS'2016: beta-risk: a New Surrogate Risk for Learning from Weakly Labeled Data
- 2015: A Morgan and Claypool Publishers book on Metric Learning (see a shorter arXiv version)
• Short Bio • Research Interests • Teaching • Bibliography • Administration Activities • Student Supervision •
Short bio
- 2002-: Professor of computer science at Jean Monnet University, Saint-Etienne.
- 2001: HDR in Computer Science (Accreditation to lead research), Jean Monnet University, Saint-Etienne.
- 1996: PhD Thesis in Computer Science, University of Lyon I
- 1994: MSc in Computer Sience ("DEA Informatique Fondamentale"), Ecole Normale Supérieure de Lyon
Research Interests
Machine Learning
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Ongoing Projects as Coordinator
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Teaching
- Statistics and Probabilities - L3 (BSc.) in Computer Science
- Data Analysis - Master 1 MLDM
- Introduction to Machine Learning - Master 1 MLDM
- Advanced Machine Learning - Master 2 MLDM
Bibliography
See DBLP, List of papers and Google ScholarAdministration Activities
- 12/2023/.. Head of the Inria project-team MALICE.
- 2016/2026 Deputy-director of the UMR CNRS Hubert Curien laboratory.
- 2010/.. Coordinator of the international Machine Learning and Data Mining master program.
- 2010/2016 Head of the Computer Science and Image Processing Department of the UMR CNRS Hubert Curien laboratory.
- 2010/2015 Head of the research group in Machine Learning - UMR CNRS Hubert Curien laboratory.
- 2006/2009 Deputy-director of the UMR CNRS Hubert Curien laboratory.
- 2008/2020: Member of the board of directors of the Jean Monnet University.
- 2006/2008: Member of the scientific board of the Jean Monnet University.
- 2004/2006: Member of the doctoral school board of the Jean Monnet University.
- 2005-/2008: Head of the Web Intelligence Master (Computer Science, Machine Learning, Pattern Recognition, Data Mining, etc.)
PhD (co)-supervision
PhD students - Post-docs- Fayad Ali Banna - Physics-guided Machine Learning, (starting date: November 2022 - co-supervised with JP. Colombier and R. Emonet).
- Antoine Caradot - Quadrature rules and adaptive sampling for PINNs , (2024-2025 with R. Emonet and A. Habrard).
- Rehan Juhboo - MAchine Learning for high definition BOne digital Twin, (co-supervised with A. Guignandon), (defended in January 2024).
- Rémi Viola - Machine Learning in Imbalanced Scenarios, (with DGIP - co-supervised with A. Habrard), (defended in June 2022).
- Tanguy Kerdoncuff - Contributions to Optimal Transport for Machine Learning: Ground Metric and Generalized Framework (co-supervised with R. Emonet), (defended in December 2021).
- Amélie Barbe - Diffusion-Wasserstein Distances for Attributed Graphs (co-supervised with P. Goncalves and P. Borgnat) (defended in December 2021). .
- Léo Gautheron - Representation learning from highly imbalanced data: application to anomaly and fraud detection (co-supervised with A. Habrard), (defended in September, 2020).
- Jordan Frery - Ensemble methods for bank fraud detection, (defended in September, 2019).
- Guillaume Meltzer - Outlier detection and fraudster profile identification in bank fraud analysis (co-supervised with A. Habrard and E. Fromont), (defended in September, 2019).
- Valentina Zantedeschi - Machine Learning from weakly labeled data (co-supervised with R. Emonet) (defended in December, 2018).
- Irina Nicolae - New Theoretical Frameworks in Metric Learning: Application to Energy Management (co-supervised with E. Gaussier), (defended in december 2016).
- Jean Philippe Peyrache New models in Domain Adaptation, (defended in July, 2014).
- Aurélien Bellet Supervised Metric Learning with Generalization Guarantees (co-supervised with A. Habrard), (defended in december, 2012, AFIA best PhD award in Artificial Intelligence).
- Laurent Boyer Using background knowledge for learning similarities between structured data (co-supervised with A. Habrard), (defended in march, 2011).
- Stéphanie Jacquemont Relationships between Sequence Mining and Grammatical Inference (co-supervised with F. Jacquenet), (defended in december, 2008).
- Henri Maxime Suchier New contributions in Boosting to deal with noisy data, (defended in june, 2006).
- Amaury Habrard Models and Techniques in Probabilistic Grammatical Inference: Dealing with Noisy Data and Knowledge Discovery (co-supervised with M. Bernard), (defended in december, 2004).
- Rémi Viola - Machine Learning in Imbalanced Scenarios, (with DGIP - co-supervised with A. Habrard), (defended in June 2022).