Proximal Gradient Optimization using Stochastic Approximation
Ideas behind its proof of convergence.
Machine learning research passionate
With a background in Applied Mathematics, I am particularly passionate about Reinforcement learning, Time series analysis and Graph signal processing, with applications to biological and engineering systems.
My resume can be downloaded here .
As a Mathematics, Vision, Learning (MVL) Master's student at École Normale Supérieure (ENS) Paris-Saclay, these are some of the classes I particularly liked this year:
I have recently started writing medium articles and tutorials in which I share and explain classical but also state-of-the-art machine learning algorithms, methods and insights. Feel free follow me on medium if you're interested by such topics !
Ideas behind its proof of convergence.
An interesting a posteriori confidence score.
Article discussing generalization inequalities for ML algorithms.
Article discussing generalization inequalities for ML algorithms.
Tutorial on a classical statistical prediction method, which sometimes serves as a good benchmark.
Recommendation letter by my M1 training director, Prof. Gilles Blanchard, can be found here.
Additional recommendation letters by two of my last year professors can be found here.
My professors contact details can be found on their webpages: Prof. Giraud's and
Prof. Enriquez's.