75 citations · 320 across the 31 of their papers we have counts for
36 papers
Distribution-free uncertainty quantification for inverse problems: application to weak lensing mass mapping
Hubert Leterme, Jalal Fadili, Jean-Luc Starck
In inverse problems, distribution-free uncertainty quantification (UQ) aims to obtain error bars with coverage guarantees that are independent of any prior assumptions about the da…
Inertial Quasi-Newton Methods for Monotone Inclusion: Efficient Resolvent Calculus and Primal-Dual Methods
Shida Wang, Jalal Fadili, Peter Ochs
We introduce an inertial quasi-Newton Forward-Backward Splitting Algorithm to solve a class of monotone inclusion problems. While the inertial step is computationally cheap, in gen…
An SDE perspective on stochastic convex optimization
Rodrigo Maulen-Soto, Jalal Fadili, Hedy Attouch
We analyze the global and local behavior of gradient-like flows under stochastic errors towards the aim of solving convex optimization problems with noisy gradient input. We first…
A Stochastic Bregman Primal-Dual Splitting Algorithm for Composite Optimization
Antonio Silveti-Falls, Cesare Molinari, Jalal Fadili
We study a stochastic first order primal-dual method for solving convex-concave saddle point problems over real reflexive Banach spaces using Bregman divergences and relative smoot…
Sharp, strong and unique minimizers for low complexity robust recovery
Jalal Fadili, Tran T. A. Nghia, Trinh T. T. Tran
In this paper, we show the important roles of sharp minima and strong minima for robust recovery. We also obtain several characterizations of sharp minima for convex regularized op…
Convergence of iterates for first-order optimization algorithms with inertia and Hessian driven damping
Hedy Attouch, Zaki Chbani, Jalal Fadili +1
In a Hilbert space setting, for convex optimization, we show the convergence of the iterates to optimal solutions for a class of accelerated first-order algorithms. They can be int…