14 citations · 20 across the 4 of their papers we have counts for
4 papers
Constructive approaches to concentration inequalities with independent random variables
Celine Moucer, Adrien Taylor, Francis Bach
Concentration inequalities, a major tool in probability theory, quantify how much a random variable deviates from a certain quantity. This paper proposes a systematic convex optimi…
Geometry-dependent matching pursuit: a transition phase for convergence on linear regression and LASSO
Céline Moucer, Adrien Taylor, Francis Bach
Greedy first-order methods, such as coordinate descent with Gauss-Southwell rule or matching pursuit, have become popular in optimization due to their natural tendency to propose s…
A systematic approach to Lyapunov analyses of continuous-time models in convex optimization
Céline Moucer, Adrien Taylor, Francis Bach
First-order methods are often analyzed via their continuous-time models, where their worst-case convergence properties are usually approached via Lyapunov functions. In this work,…
PEPit: computer-assisted worst-case analyses of first-order optimization methods in Python
Baptiste Goujaud, Céline Moucer, François Glineur +3
PEPit is a Python package aiming at simplifying the access to worst-case analyses of a large family of first-order optimization methods possibly involving gradient, projection, pro…