A convergent least-squares regularized blind deconvolution approach. - Anastasia Cornelio; Federica Porta; Marco Prato (Appl. Math. Comput., 2015)

On some steplength approaches for proximal algorithms. - Federica Porta; Ignace Loris (Appl. Math. Comput., 2015)

Limited-memory scaled gradient projection methods for real-time image deconvolution in microscopy. - Federica Porta; Riccardo Zanella; Gaetano Zanghirati; Luca Zanni (Commun. Nonlinear Sci. Numer. Simul., 2015)

A New Steplength Selection for Scaled Gradient Methods with Application to Image Deblurring. - Federica Porta; Marco Prato; Luca Zanni (J. Sci. Comput., 2015)

Variable Metric Inexact Line-Search-Based Methods for Nonsmooth Optimization. - Silvia Bonettini; Ignace Loris; Federica Porta; Marco Prato (SIAM J. Optim., 2016)

A Variable Metric Forward-Backward Method with Extrapolation. - Silvia Bonettini; Federica Porta; Valeria Ruggiero (SIAM J. Sci. Comput., 2016)

A nonsmooth regularization approach based on shearlets for Poisson noise removal in ROI tomography. - Tatiana A. Bubba; Federica Porta; Gaetano Zanghirati; Silvia Bonettini (Appl. Math. Comput., 2018)

Serial and parallel approaches for image segmentation by numerical minimization of a second-order functional. - Riccardo Zanella; Federica Porta; Valeria Ruggiero; Massimo Zanetti (Appl. Math. Comput., 2018)

A Limited Memory Gradient Projection Method for Box-Constrained Quadratic Optimization Problems. - Serena Crisci; Federica Porta; Valeria Ruggiero; Luca Zanni (NUMTA(1), 2019)

Spectral Properties of Barzilai-Borwein Rules in Solving Singly Linearly Constrained Optimization Problems Subject to Lower and Upper Bounds. - Serena Crisci; Federica Porta; Valeria Ruggiero; Luca Zanni (SIAM J. Optim., 2020)

Upper Extremity Functional Rehabilitation for Stroke Survivors Using Error-Augmented Visual Feedback: Interim Results. - Federica Porta; Courtney Celian; James L. Patton (EMBC, 2021)

Combining Weighted Total Variation and Deep Image Prior for natural and medical image restoration via ADMM. - Pasquale Cascarano; Andrea Sebastiani; Maria Colomba Comes; Giorgia Franchini; Federica Porta (ICCSA (Workshops), 2021)

Variable metric techniques for forward-backward methods in imaging. - Silvia Bonettini; Federica Porta; Valeria Ruggiero; Luca Zanni (J. Comput. Appl. Math., 2021)

Neural network-based classification of ENG recordings in response to naturally evoked stimulation. - Antonio Coviello; Federica Porta; Maurizio Magarini; Umberto Spagnolini (NANOCOM, 2022)

Biomedical Image Classification via Dynamically Early Stopped Artificial Neural Network. - Giorgia Franchini; Micaela Verucchi; Ambra Catozzi; Federica Porta; Marco Prato (Algorithms, 2022)

Line Search Stochastic Gradient Algorithm with A-priori Rule for Monitoring the Control of the Variance. - Giorgia Franchini; Federica Porta; Valeria Ruggiero; Ilaria Trombini; Luca Zanni (NUMTA (1), 2023)

Diagonal Barzilai-Borwein Rules in Stochastic Gradient-Like Methods. - Giorgia Franchini; Federica Porta; Valeria Ruggiero; Ilaria Trombini; Luca Zanni (OLA, 2023)

Piece-wise Constant Image Segmentation with a Deep Image Prior Approach. - Alessandro Benfenati; Ambra Catozzi; Giorgia Franchini; Federica Porta (SSVM, 2023)

Constrained and unconstrained deep image prior optimization models with automatic regularization. - Pasquale Cascarano; Giorgia Franchini; Erich Kobler; Federica Porta; Andrea Sebastiani (Comput. Optim. Appl., 2023)

Hybrid limited memory gradient projection methods for box-constrained optimization problems. - Serena Crisci; Federica Porta; Valeria Ruggiero; Luca Zanni (Comput. Optim. Appl., 2023)

A Line Search Based Proximal Stochastic Gradient Algorithm with Dynamical Variance Reduction. - Giorgia Franchini; Federica Porta; Valeria Ruggiero; Ilaria Trombini (J. Sci. Comput., 2023)

Correction to: A Line Search Based Proximal Stochastic Gradient Algorithm with Dynamical Variance Reduction. - Giorgia Franchini; Federica Porta; Valeria Ruggiero; Ilaria Trombini (J. Sci. Comput., 2023)

A variable metric proximal stochastic gradient method: An application to classification problems. - Pasquale Cascarano; Giorgia Franchini; Erich Kobler; Federica Porta; Andrea Sebastiani (EURO J. Comput. Optim., 2024)

A stochastic gradient method with variance control and variable learning rate for Deep Learning. - Giorgia Franchini; Federica Porta; Valeria Ruggiero; Ilaria Trombini; Luca Zanni (J. Comput. Appl. Math., 2024)

Early stopping strategies in Deep Image Prior. - Alessandro Benfenati; Ambra Catozzi; Giorgia Franchini; Federica Porta (Soft Comput., 2025)