Luca Zanni

About Luca Zanni

Luca Zanni, With an exceptional h-index of 23 and a recent h-index of 16 (since 2020), a distinguished researcher at Università degli Studi di Modena e Reggio Emilia, specializes in the field of Numerical Analysis, Numerical Optimization, Inverse problems, Image reconstruction, Machine learning.

His recent articles reflect a diverse array of research interests and contributions to the field:

Diagonal Barzilai-Borwein Rules in Stochastic Gradient-Like Methods

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

Neural architecture search via standard machine learning methodologies

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

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

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

Barzilai-Borwein and Ritz-like values in steplength selections strategies for stochastic gradient methods

Variable metric techniques for forward–backward methods in imaging

Luca Zanni Information

University

Position

Professor of Numerical Analysis Italy

Citations(all)

2603

Citations(since 2020)

819

Cited By

2115

hIndex(all)

23

hIndex(since 2020)

16

i10Index(all)

38

i10Index(since 2020)

26

Email

University Profile Page

Università degli Studi di Modena e Reggio Emilia

Google Scholar

View Google Scholar Profile

Luca Zanni Skills & Research Interests

Numerical Analysis

Numerical Optimization

Inverse problems

Image reconstruction

Machine learning

Top articles of Luca Zanni

Title

Journal

Author(s)

Publication Date

Diagonal Barzilai-Borwein Rules in Stochastic Gradient-Like Methods

Giorgia Franchini

Federica Porta

Valeria Ruggiero

Ilaria Trombini

Luca Zanni

2023/5/3

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

Computational Optimization and Applications

Serena Crisci

Federica Porta

Valeria Ruggiero

Luca Zanni

2023/1

Neural architecture search via standard machine learning methodologies

Mathematics in Engineering

Giorgia Franchini

Ruggiero Valeria

Federica Porta

Luca Zanni

2023

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

Applied Mathematics in Science and Engineering

Giorgia Franchini

Federica Porta

Valeria Ruggiero

Ilaria Trombini

Luca Zanni

2023/12/31

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

SIAM JOURNAL ON OPTIMIZATION

S Crisci

Federica Porta

Valeria Ruggiero

Luca Zanni

2023/12/3

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

ANNALI DELL'UNIVERSITA'DI FERRARA

Serena Crisci

Federica Porta

Valeria Ruggiero

Luca Zanni

2022/11

Barzilai-Borwein and Ritz-like values in steplength selections strategies for stochastic gradient methods

PROCEEDINGS OF SIMAI 2020+ 21

Giorgia Franchini

Federica Porta

Valeria Ruggiero

Luca Zanni

2021/10/31

Variable metric techniques for forward–backward methods in imaging

Journal of Computational and Applied Mathematics

Silvia Bonettini

Federica Porta

Valeria Ruggiero

Luca Zanni

2021/3/15

Ritz-like values in gradient projection methods for box-constrained optimization problems

PROCEEDINGS OF SIMAI 2020+ 21

Serena Crisci

Federica Porta

Valeria Ruggiero

Luca Zanni

2021/10/31

GPU acceleration of a model-based iterative method for Digital Breast Tomosynthesis

Scientific reports

R Cavicchioli

J Cheng Hu

E Loli Piccolomini

E Morotti

L Zanni

2020/1/8

Hyperparameters setting in Stochastic Optimisation Methods

Luca Zanni

2020

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

SIAM Journal on Optimization

Serena Crisci

Federica Porta

Valeria Ruggiero

Luca Zanni

2020

Ritz-like values in steplength selections for stochastic gradient methods

Soft Computing

Giorgia Franchini

Valeria Ruggiero

Luca Zanni

2020/12

Artificial Neural Networks: the missing link between curiosity and accuracy

Giorgia Franchini

Paolo Burgio

Luca Zanni

2020

Steplength and mini-batch size selection in stochastic gradient methods

Giorgia Franchini

Valeria Ruggiero

Luca Zanni

2020/7/19

A Transdisciplinary digital approach for tractor’s human-centred design

International Journal of Computer Integrated Manufacturing

Fabio Grandi

Luca Zanni

Margherita Peruzzini

Marcello Pellicciari

Claudia Elisabetta Campanella

2020/4/2

See List of Professors in Luca Zanni University(Università degli Studi di Modena e Reggio Emilia)