Learning rate selection in stochastic gradient methods based on line search strategies

Special issue for SIMAI 2020–2021: large-scale optimization and applications

Neural blind deconvolution with Poisson data

A Line Search Based Proximal Stochastic Gradient Algorithm with Dynamical Variance Reduction

Neural architecture search via standard machine learning methodologies

Correction to: A Line Search Based Proximal Stochastic Gradient Algorithm with Dynamical Variance Reduction (Journal of Scientific Computing, (2023), 94, 1, (23), 10.1007/s10915-022-02084-3)

Hybrid limited memory gradient projection methods for box-constrained optimization problems

On the convergence properties of scaled gradient projection methods with non-monotone Armijo–like line searches

Editorial: Special issue mathematical methods and numerical computations in honor of Ilio Galligani

Variable metric techniques for forward–backward methods in imaging

A Regularized Affine-Scaling Trust-Region Method for Parametric Imaging of Dynamic PET Data

Spectral properties of barzilai-borwein rules in solving singly linearly constrained optimization problems subject to lower and upper bounds

Ritz-like values in steplength selections for stochastic gradient methods

Steplength selection in gradient projection methods for box-constrained quadratic programs

On the steplength selection in gradient methods for unconstrained optimization

Serial and parallel approaches for image segmentation by numerical minimization of a second-order functional

Roof planes detection via a second-order variational model

Inertial variable metric techniques for the inexact forward-backward algorithm

Introduction to the special issue for SIMAI 2016

Runge–Kutta-like scaling techniques for first-order methods in convex optimization