3 citations · 5 across the 11 of their papers we have counts for
4 papers · 2 filters
Gradient correlation is a key ingredient to accelerate SGD with momentum
Julien Hermant, Marien Renaud, Jean-François Aujol +2
Empirically, it has been observed that adding momentum to Stochastic Gradient Descent (SGD) accelerates the convergence of the algorithm. However, the literature has been rather pe…
Strong Convergence of FISTA Iterates under H{ö}lderian and Quadratic Growth Conditions
Jean-François Aujol, Charles Dossal, Hippolyte Labarrière +1
Introduced by Beck and Teboulle, FISTA (for Fast Iterative Shrinkage-Thresholding Algorithm) is a first-order method widely used in convex optimization. Adapted from Nesterov's acc…
Study of the behaviour of Nesterov Accelerated Gradient in a non convex setting: the strongly quasar convex case
Julien Hermant, Jean-François Aujol, Charles Dossal +1
We study the convergence of Nesterov Accelerated Gradient (NAG) minimization algorithmapplied to a class of non convex functions called strongly quasar convex functions. We show th…
Heavy Ball Momentum for Non-Strongly Convex Optimization
Jean-François Aujol, Charles Dossal, Hippolyte Labarrière +1
When considering the minimization of a quadratic or strongly convex function, it is well known that first-order methods involving an inertial term weighted by a constant-in-time pa…