 |
«Ignorance leads to fear, fear
leads to hatred and hatred leads to violence. That's the equation» (Ibn Roshd, Averroès, 1126-1198) « Raise your words, not voice. It is rain that grows flowers, not thunder » (Jalal Ad-Din Rumi, 1207-1273) «Knowledge acquired in a foreign country can be a homeland and ignorance can be an exile lived in one's own country» (Ibn Roshd, Averroès, 1126-1198) |
Younès Bennani received
his PhD in Machine Learning from Paris-Saclay
University. He is
currently Full Professor of Computer Science at Sorbonne Paris Nord University. Younès Bennani
research interests are in Machine Learning and Data Science. His
research focuses on unsupervised learning,
deep learning, and collaborative clustering. His recent work deals with
the
representations learning, federated
learning, transfer learning and domain
adaptation. He
is the founder and scientific director (from 2005 to 2011) of a team
whose main theme is Machine Learning and
Applications at the
computer science lab. of Paris-Nord (LIPN - UMR 7030 CNRS). He has published 3
books and approximately 300 papers in refereed conferences proceedings
or journals or as contributions in books. Younès Bennani is
the Vice-President for Digital Transformation at the Sorbonne Paris
Nord
University - Ministère
de l'Enseignement Supérieur, de la Recherche et de l'Innovation.
Latest research:
«A survey on domain adaptation theory: learning bounds and theoretical guarantees», CoRR abs/2004.11829, 2020.
«Advances in Domain Adaptation Theory», ISBN: 9781785482366 - ISTE - Elsevier, 2019.
«A new sparse representation learning of complex data: application to dynamic clustering of web navigation», Pattern Recognition (The journal of Pattern Recognition Society), Elsevier, 2019.
«Collaborative
Clustering: Why, When, What and How»,
International Journal on
Information Fusion (Information Fusion), Elsevier, January
2018.
«Co-clustering through Optimal Transport», International Conference on Machine Learning (ICML'2017), Australia.
Scientific events:
- ISCV: «International Conference on Intelligent Systems and Computer Vision» IEEE conference.
- ETP: «Deep Learning & Data Science» Ecole Thématique de Printemps.
- CIF-SD: Conférence Internationale Francophone sur la Science des Données
- H2DM: International Workshop on High Dimensional Data Mining
