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)

On the convergence of inexact augmented Lagrangian methods for problems with convex constraints. - Giulio Galvan; Matteo Lapucci (Oper. Res. Lett., 2019)

An augmented Lagrangian algorithm for multi-objective optimization. - Guido Cocchi; Matteo Lapucci (Comput. Optim. Appl., 2020)

An Alternating Augmented Lagrangian method for constrained nonconvex optimization. - Giulio Galvan; Matteo Lapucci; Tommaso Levato; Marco Sciandrone (Optim. Methods Softw., 2020)

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)

Pareto front approximation through a multi-objective augmented Lagrangian method. - Guido Cocchi; Matteo Lapucci; Pierluigi Mansueto (EURO J. Comput. Optim., 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)

Convergent Inexact Penalty Decomposition Methods for Cardinality-Constrained Problems. - Matteo Lapucci; Tommaso Levato; Marco Sciandrone (J. Optim. Theory Appl., 2021)

A study on sequential minimal optimization methods for standard quadratic problems. - Riccardo Bisori; Matteo Lapucci; Marco Sciandrone (4OR, 2022)

A penalty decomposition approach for multi-objective cardinality-constrained optimization problems. - Matteo Lapucci (Optim. Methods Softw., 2022)

Loss-Optimal Classification Trees: A Generalized Framework and the Logistic Case. - Tommaso Aldinucci; Matteo Lapucci (CoRR, 2023)

A limited memory Quasi-Newton approach for multi-objective optimization. - Matteo Lapucci; Pierluigi Mansueto (Comput. Optim. Appl., 2023)

Improved front steepest descent for multi-objective optimization. - Matteo Lapucci; Pierluigi Mansueto (Oper. Res. Lett., 2023)

A memetic procedure for global multi-objective optimization. - Matteo Lapucci; Pierluigi Mansueto; Fabio Schoen (Math. Program. Comput., 2023)

Inexact penalty decomposition methods for optimization problems with geometric constraints. - Christian Kanzow; Matteo Lapucci (Comput. Optim. Appl., 2023)

A Unifying Framework for Sparsity-Constrained Optimization. - Matteo Lapucci; Tommaso Levato; Francesco Rinaldi; Marco Sciandrone (J. Optim. Theory Appl., 2023)

Convergence Conditions for Stochastic Line Search Based Optimization of Over-parametrized Models. - Matteo Lapucci; Davide Pucci (CoRR, 2024)

Effectively Leveraging Momentum Terms in Stochastic Line Search Frameworks for Fast Optimization of Finite-Sum Problems. - Matteo Lapucci; Davide Pucci (CoRR, 2024)

Optimization-Driven Design of Monolithic Soft-Rigid Grippers. - Pierluigi Mansueto; Mihai Dragusanu; Anjum Saeed; Monica Malvezzi; Matteo Lapucci; Gionata Salvietti (CoRR, 2024)

Advances in nonlinear optimization and equilibrium problems - Special issue editorial. - Matteo Lapucci; Fabio Schoen (EURO J. Comput. Optim., 2024)

Convergence and complexity guarantees for a wide class of descent algorithms in nonconvex multi-objective optimization. - Matteo Lapucci (Oper. Res. Lett., 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., 2024)

Cardinality-Constrained Multi-objective Optimization: Novel Optimality Conditions and Algorithms. - Matteo Lapucci; Pierluigi Mansueto (J. Optim. Theory Appl., 2024)

On the Convergence of Inexact Alternate Minimization in Problems with ℓ 0 Penalties. - Matteo Lapucci; Alessio Sortino (Oper. Res. Forum, 2024)

A Robust Initialization of Residual Blocks for Effective ResNet Training Without Batch Normalization. - Enrico Civitelli; Alessio Sortino; Matteo Lapucci; Francesco Bagattini; Giulio Galvan (IEEE Trans. Neural Networks Learn. Syst., 2025)