My research interests include constrained, multi-objective and sparse non-linear optimization and optimization methods for machine learning and statistics.
- An augmented Lagrangian algorithm for multi-objective optimization.
G. Cocchi, M. Lapucci.
Computational Optimization and Applications (2020).
- An efficient optimization approach for best subset selection in linear regression, with application to model selection and fitting in autoregressive time-series.
L. Di Gangi, M. Lapucci, F. Schoen, A. Sortino
Computational Optimization and Applications (2019).
- On the convergence of inexact Augmented Lagrangian methods for problems with convex constraints.
G. Galvan, M. Lapucci
Operations Research Letters (2019).
- An Alternating Augmented Lagrangian method for constrained nonconvex optimization.
G. Galvan, M. Lapucci, T. Levato, M. Sciandrone
Optimization Methods and Software (2019).
My ORCID number: 0000-0002-2488-5486
- ODS 2019 (Genova) – An Efficient Optimization Approach for Subset Selection, with Application to Linear Regression and Auto-Regressive Time Series.
E-mail: matlapucci at gmail dot com