Matteo Lapucci

According to our database, Matteo Lapucci authored at least 19 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Cardinality-Constrained Multi-objective Optimization: Novel Optimality Conditions and Algorithms.

Matteo Lapucci, Pierluigi Mansueto

J. Optim. Theory Appl., April, 2024

Integrated task scheduling and personnel rostering of airports ground staff: A case study.

Paola Cappanera, Leonardo Di Gangi, Matteo Lapucci, Giulia Pellegrini, Marco Roma, Fabio Schoen, Alessio Sortino

Expert Syst. Appl., March, 2024

2023

A Unifying Framework for Sparsity-Constrained Optimization.

Matteo Lapucci, Tommaso Levato, Francesco Rinaldi, Marco Sciandrone

J. Optim. Theory Appl., November, 2023

Inexact penalty decomposition methods for optimization problems with geometric constraints.

Christian Kanzow, Matteo Lapucci

Comput. Optim. Appl., July, 2023

A memetic procedure for global multi-objective optimization.

Matteo Lapucci, Pierluigi Mansueto, Fabio Schoen

Math. Program. Comput., June, 2023

Improved front steepest descent for multi-objective optimization.

Matteo Lapucci, Pierluigi Mansueto

Oper. Res. Lett., May, 2023

A limited memory Quasi-Newton approach for multi-objective optimization.

Matteo Lapucci, Pierluigi Mansueto

Comput. Optim. Appl., May, 2023

Loss-Optimal Classification Trees: A Generalized Framework and the Logistic Case.

Tommaso Aldinucci, Matteo Lapucci

CoRR, 2023

2022

A penalty decomposition approach for multi-objective cardinality-constrained optimization problems.

Matteo Lapucci

Optim. Methods Softw., 2022

A study on sequential minimal optimization methods for standard quadratic problems.

Riccardo Bisori, Matteo Lapucci, Marco Sciandrone

4OR, 2022

2021

Convergent Inexact Penalty Decomposition Methods for Cardinality-Constrained Problems.

Matteo Lapucci, Tommaso Levato, Marco Sciandrone

J. Optim. Theory Appl., 2021

A Two-Level Decomposition Framework Exploiting First and Second Order Information for SVM Training Problems.

Giulio Galvan, Matteo Lapucci, Chih-Jen Lin, Marco Sciandrone

J. Mach. Learn. Res., 2021

Pareto front approximation through a multi-objective augmented Lagrangian method.

Guido Cocchi, Matteo Lapucci, Pierluigi Mansueto

EURO J. Comput. Optim., 2021

A Robust Initialization of Residual Blocks for Effective ResNet Training without Batch Normalization.

Enrico Civitelli, Alessio Sortino, Matteo Lapucci, Francesco Bagattini, Giulio Galvan

CoRR, 2021

An effective procedure for feature subset selection in logistic regression based on information criteria.

Enrico Civitelli, Matteo Lapucci, Fabio Schoen, Alessio Sortino

Comput. Optim. Appl., 2021

2020

An Alternating Augmented Lagrangian method for constrained nonconvex optimization.

Giulio Galvan, Matteo Lapucci, Tommaso Levato, Marco Sciandrone

Optim. Methods Softw., 2020

An augmented Lagrangian algorithm for multi-objective optimization.

Guido Cocchi, Matteo Lapucci

Comput. Optim. Appl., 2020

2019

On the convergence of inexact augmented Lagrangian methods for problems with convex constraints.

Giulio Galvan, Matteo Lapucci

Oper. Res. Lett., 2019

An efficient optimization approach for best subset selection in linear regression, with application to model selection and fitting in autoregressive time-series.

Leonardo Di Gangi, Matteo Lapucci, Fabio Schoen, Alessio Sortino

Comput. Optim. Appl., 2019