Quentin BERTRAND - Home

I am a 2nd year PhD student in machine learning at Inria Paris-Saclay (in the Parietal Team), under the supervision of Joseph Salmon and Alexandre Gramfort. I work on the optimization and statistical aspects of high dimensional sparse linear regression applied to brain signals reconstruction. I have a keen interest in the Python programming language: I am a contributor to MNE. I also develop a python package for automatic hyperparameter selection of sparse linear models. Here is a short resume and my list of publications.

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Upcoming events

• August 26-28: I will present our paper on support recovery and sup-norm convergence rates for sparse pivotal estimation at AISTATS 2020 see you there! (virtually)

Past events

• July 12-19: I presented our work on Implicit differentiation of Lasso-type models for hyperparameter optimization at ICML2020 (virtually)

• June 28 - July 10, 2020: I attended the Machine Learning Summer School (MLSS) (virtually)

• January 6, 2020: our paper Support recovery and sup-norm convergence rates for sparse pivotal estimation was accepted to AISTATS 2020 in Palermo, Italy

• December 8-15, 2019: I presented our paper Handling correlated and repeated measurements with the smoothed multivariate square-root Lasso at NeurIPS2019 in Vancouver, Canada

• December 3-4, 2019: I gave a 20min talk on our paper Support recovery and sup-norm convergence rates for sparse pivotal estimation at PGMO days in Palaiseau, France

• October 21-25, 2019: I was awarded a grant from GDR IA to visit Samuel Vaiter in Dijon, France

• October 16-18, 2019: I participated, and gave a 20min oral presentation at Journées du GDR MOA 2019 in Rennes, France