I am a postdoctoral researcher at Orange Labs in Vincent Lemaire’s group.
My research interests include weakly supervised learning and generalization in deep neural networks. I am interested in trying to build bridges between deep learning training mechanisms and more established machine learning techniques such as linear models and ensemble methods.
I did my PhD at Mila in Québec, under the joint supervision of Pascal Vincent and Guillaume Lajoie. Previously, I was a multiple hats engineer at Eco-Adapt where I worked with time series from various industrial sensors, trying to develop automated algorithms to make sense of these data streams. Prior to that I studied at École des Mines.
Here is my academic CV.
|Apr 20, 2023||I successfully defended my PhD Thesis: Deep networks training and generalization: insights from linearization (manuscript, slides) 🥳|
|Dec 21, 2022||Our paper Lazy vs hasty: linearization in deep networks impacts learning schedule based on example difficulty was accepted to TMLR. (code)|
|Sep 23, 2022||New pre-print Lazy vs hasty: linearization in deep networks impacts learning schedule based on example difficulty available.|
|Jul 22, 2022||I will present our recent work Lazy vs hasty: linearization in deep networks impacts learning schedule based on example difficulty (paper, poster) at the SCIS workshop at ICML 2022.|
|Jul 23, 2021||Presentation of our workshop paper Continual learning and Deep Networks: an Analysis of the Last Layer with Timothée Lesort at the Theory of Continual Learning workshop at ICML.|