lapucciPhD Student of Smart Computing at Dipartimento di Ingegneria dell’Informazione, Università degli Studi di Firenze.

My research interests include constrained, multi-objective and sparse non-linear optimization and optimization methods for machine learning and statistics.


  1. An augmented Lagrangian algorithm for multi-objective optimization.
    G. Cocchi, M. Lapucci.
    Computational Optimization and Applications (2020).
    DOI: 10.1007/s10589-020-00204-z
  2. 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).
    DOI: 10.1007/s10589-019-00134-5
  3. On the convergence of inexact Augmented Lagrangian methods for problems with convex constraints.
    G. Galvan, M. Lapucci
    Operations Research Letters (2019).
    DOI: 10.1016/j.orl.2019.03.006
  4. An Alternating Augmented Lagrangian method for constrained nonconvex optimization.
    G. Galvan, M. Lapucci, T. Levato, M. Sciandrone
    Optimization Methods and Software (2019).
    DOI: 10.1080/10556788.2019.1576177

My ORCID number: 0000-0002-2488-5486


  1. ODS 2019 (Genova) An Efficient Optimization Approach for Subset Selection, with Application to Linear Regression and Auto-Regressive Time Series.


Via di Santa Marta, 3 – 50139 Firenze FI (Italy)

E-mail: matlapucci at gmail dot com