We propose and analyze the convergence of a novel stochastic algorithm for monotone
inclusions that are sum of a maximal monotone operator and a single-valued cocoercive …

We consider a variable metric and inexact version of the fast iterative soft-thresholding
algorithm (FISTA) type algorithm considered in [L. Calatroni and A. Chambolle, SIAM J …

We study a general convex optimization problem, which covers various classic problems in
different areas and particularly includes many optimal transport related problems arising in …

We present a forward-backward-based algorithm to minimize a sum of a differentiable
function and a nonsmooth function, both being possibly nonconvex. The main contribution of …

Rate of convergence of inertial gradient dynamics with time-dependent viscous damping
coefficient Page 1 HAL Id: hal-01660062 https://hal.archives-ouvertes.fr/hal-01660062v2 …

This paper deals with a general framework for inexact forward--backward algorithms aimed
at minimizing the sum of an analytic function and a lower semicontinuous, subanalytic …

One of the most popular approaches for the minimization of a convex functional given by the
sum of a differentiable term and a nondifferentiable one is the forward-backward method …

In a Hilbert space setting, in order to develop fast first-order methods for convex optimization,
we study the asymptotic convergence properties (t→+∞) of the trajectories of the inertial …

In this paper, we develop rapidly convergent forward-backward algorithms for computing
zeroes of the sum of finitely many maximally monotone operators. A modification of the …

We study inexact fixed-point proximity algorithms for solving a class of sparse regularization
problems involving the ℓ 0 norm. Specifically, the ℓ 0 model has an objective function that is …