16 citations · 29 across the 14 of their papers we have counts for
8 papers · 1 filter
Differentiating Minimal-Norm Solutions to Parametric Optimization Problems
Baptiste Plaquevent-Jourdain, Jalal Fadili, Antonio Silveti-Falls
Differentiating through parametric optimization problems is central to bilevel programming and meta-learning, often accomplished using approximate implicit differentiation. The imp…
Frank-Wolfe with Moreau Envelope Smoothing for Nonsmooth Nonconvex Problems
Antonio Silveti-Falls, Cesare Molinari, Zev Woodstock
We present and analyze Frank-Wolfe with Moreau Envelope Smoothing (FRAMES) for solving nonsmooth nonconvex constrained optimization problems, taking advantage of iterative smoothin…
Boosted Stochastic Frank-Wolfe for Constrained Nonconvex Optimization
Navil Nandhan, Abbas Khademi, Antonio Silveti-Falls
The boosted Frank-Wolfe algorithm accelerates the classical Frank-Wolfe algorithm by better aligning the update direction with the negative gradient. Its analysis, however, has bee…
Constrained Stochastic Spectral Preconditioning Converges for Nonconvex Objectives
Konstantinos Oikonomidis, Jan Quan, Kimon Antonakopoulos +3
In this work, we develop proximal preconditioned gradient methods with a focus on spectral gradient methods providing a proximal extension to the Muon and Scion optimizers. We intr…
Adaptive Conditional Gradient Descent
Abbas Khademi, Antonio Silveti-Falls
Selecting an effective step-size is a fundamental challenge in first-order optimization, especially for problems with non-Euclidean geometries. This paper presents a novel adaptive…
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…
Inexact and Stochastic Generalized Conditional Gradient with Augmented Lagrangian and Proximal Step
Antonio Silveti-Falls, Cesare Molinari, Jalal Fadili
In this paper we propose and analyze inexact and stochastic versions of the CGALP algorithm developed in the authors' previous paper, which we denote ICGALP, that allows for errors…
Generalized Conditional Gradient with Augmented Lagrangian for Composite Minimization
Antonio Silveti-Falls, Cesare Molinari, Jalal Fadili
In this paper we propose a splitting scheme which hybridizes generalized conditional gradient with a proximal step which we call CGALP algorithm, for minimizing the sum of three pr…