109 citations · 280 across the 31 of their papers we have counts for
7 papers · 1 filter
Quadratic minimization: from conjugate gradient to an adaptive Heavy-ball method with Polyak step-sizes
Baptiste Goujaud, Adrien Taylor, Aymeric Dieuleveut
In this work, we propose an adaptive variation on the classical Heavy-ball method for convex quadratic minimization. The adaptivity crucially relies on so-called "Polyak step-sizes…
Convergence of Proximal Point and Extragradient-Based Methods Beyond Monotonicity: the Case of Negative Comonotonicity
Eduard Gorbunov, Adrien Taylor, Samuel Horváth +1
Algorithms for min-max optimization and variational inequalities are often studied under monotonicity assumptions. Motivated by non-monotone machine learning applications, we follo…
Optimal first-order methods for convex functions with a quadratic upper bound
Baptiste Goujaud, Adrien Taylor, Aymeric Dieuleveut
We analyze worst-case convergence guarantees of first-order optimization methods over a function class extending that of smooth and convex functions. This class contains convex fun…
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,…
Fast Stochastic Composite Minimization and an Accelerated Frank-Wolfe Algorithm under Parallelization
Benjamin Dubois-Taine, Francis Bach, Quentin Berthet +1
We consider the problem of minimizing the sum of two convex functions. One of those functions has Lipschitz-continuous gradients, and can be accessed via stochastic oracles, wherea…
Last-Iterate Convergence of Optimistic Gradient Method for Monotone Variational Inequalities
Eduard Gorbunov, Adrien Taylor, Gauthier Gidel
The Past Extragradient (PEG) [Popov, 1980] method, also known as the Optimistic Gradient method, has known a recent gain in interest in the optimization community with the emergenc…
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…