93 citations · 323 across the 15 of their papers we have counts for
15 papers
PnP-IPA: A Provably Convergent Plug-and-Play Inexact Proximal Algorithm for Nonconvex Imaging Problems
Cristiano Parenti, Silvia Bonettini, Marco Prato
Plug-and-Play (PnP) methods have emerged as a highly effective paradigm for solving imaging inverse problems by replacing traditional proximity operators of regularization terms wi…
Algorithmic unfolding for image reconstruction and localization problems in fluorescence microscopy
Silvia Bonettini, Luca Calatroni, Danilo Pezzi +1
We propose an unfolded accelerated projected-gradient descent procedure to estimate model and algorithmic parameters for image super-resolution and molecule localization problems i…
An abstract convergence framework with application to inertial inexact forward--backward methods
Silvia Bonettini, Peter Ochs, Marco Prato +1
In this paper we introduce a novel abstract descent scheme suited for the minimization of proper and lower semicontinuous functions. The proposed abstract scheme generalizes a set…
Explainable bilevel optimization: an application to the Helsinki deblur challenge
Silvia Bonettini, Giorgia Franchini, Danilo Pezzi +1
In this paper we present a bilevel optimization scheme for the solution of a general image deblurring problem, in which a parametric variational-like approach is encapsulated withi…
On the convergence of a linesearch based proximal-gradient method for nonconvex optimization
Silvia Bonettini, Ignace Loris, Federica Porta +2
We consider a variable metric linesearch based proximal gradient method for the minimization of the sum of a smooth, possibly nonconvex function plus a convex, possibly nonsmooth t…
Numerical assessment of shearlet-based regularization in ROI tomography
Tatiana A. Bubba, Demetrio Labate, Gaetano Zanghirati +1
When it comes to computed tomography (CT), the possibility to reconstruct a small region-of-interest (ROI) using truncated projection data is particularly appealing due to its pote…
A variable metric forward--backward method with extrapolation
Silvia Bonettini, Federica Porta, Valeria Ruggiero
Forward-backward methods are a very useful tool for the minimization of a functional given by the sum of a differentiable term and a nondifferentiable one and their investigation h…
Variable metric inexact line-search based methods for nonsmooth optimization
Silvia Bonettini, Ignace Loris, Federica Porta +1
We develop a new proximal-gradient method for minimizing the sum of a differentiable, possibly nonconvex, function plus a convex, possibly non differentiable, function. The key fea…
A blind deconvolution method for ground based telescopes and Fizeau interferometers
M. Prato, A. La Camera, S. Bonettini +3
In the case of ground-based telescopes equipped with adaptive optics systems, the point spread function (PSF) is only poorly known or completely unknown. Moreover, an accurate mode…
A cyclic block coordinate descent method with generalized gradient projections
Silvia Bonettini, Marco Prato, Simone Rebegoldi
The aim of this paper is to present the convergence analysis of a very general class of gradient projection methods for smooth, constrained, possibly nonconvex, optimization. The k…
Scaling techniques for -subgradient projection methods
Silvia Bonettini, Alessandro Benfenati, Valeria Ruggiero
The recent literature on first order methods for smooth optimization shows that significant improvements on the practical convergence behaviour can be achieved with variable stepsi…
A scaled gradient projection method for Bayesian learning in dynamical systems
Silvia Bonettini, Alessandro Chiuso, Marco Prato
A crucial task in system identification problems is the selection of the most appropriate model class, and is classically addressed resorting to cross-validation or using asymptoti…
New convergence results for the scaled gradient projection method
Silvia Bonettini, Marco Prato
The aim of this paper is to deepen the convergence analysis of the scaled gradient projection (SGP) method, proposed by Bonettini et al. in a recent paper for constrained smooth op…
Accelerated gradient methods for the X-ray imaging of solar flares
S. Bonettini, M. Prato
In this paper we present new optimization strategies for the reconstruction of X-ray images of solar flares by means of the data collected by the Reuven Ramaty High Energy Solar Sp…
A convergent blind deconvolution method for post-adaptive-optics astronomical imaging
M. Prato, A. La Camera, S. Bonettini +1
In this paper we propose a blind deconvolution method which applies to data perturbed by Poisson noise. The objective function is a generalized Kullback-Leibler divergence, dependi…