Publications

1. A study on sequential minimal optimization methods for standard quadratic problems.
   R. Bisori, M. Lapucci, M. Sciandrone.
   4OR (2021).
   DOI: 10.1007/s10288-021-00496-9
2. Can machine learning models support physicians in systemic lupus erythematosus diagnosis? Results from a monocentric cohort.
   F. Ceccarelli, M. Lapucci, G. Olivieri, A. Sortino, M. Sciandrone et al.
   Joint Bone Spine (2021).
   DOI: 10.1016/j.jbspin.2021.105292
3. Pareto front approximation through a multi-objective augmented
   Lagrangian method.
   G. Cocchi, M. Lapucci, P. Mansueto.
   EURO Journal on Computational Optimization (2021).
   DOI: 10.1016/j.ejco.2021.100008
4. An effective procedure for feature subset selection in logistic regression based on information criteria.
   E. Civitelli, M. Lapucci, F. Schoen, A. Sortino.
   Computational Optimization and Applications (2021).
   DOI: 10.1007/s10589-021-00288-1
5. A Two-Level Decomposition Framework Exploiting First and Second Order Information for SVM Training Problems.
   G. Galvan, M. Lapucci, C.-J. Lin, M. Sciandrone.
   Journal of Machine Learning Research (2021).
   Link: https://jmlr.org/papers/v22/19-632.html
6. Comprehensive Disease Control in Systemic Lupus Erythematosus.
   F. Ceccarelli, G. Olivieri, A. Sortino, M. Lapucci, M. Sciandrone et al..
   Seminars in Arthritis and Rheumatism (2021).
   DOI: 10.1016/j.semarthrit.2021.02.005
7. Convergent Inexact Penalty Decomposition Methods for Cardinality-Constrained Problems.
   M. Lapucci, T. Levato, M. Sciandrone.
   Journal of Optimization Theory and Applications (2020).
   DOI: 10.1007/s10957-020-01793-9
8. An augmented Lagrangian algorithm for multi-objective optimization.
   G. Cocchi, M. Lapucci.
   Computational Optimization and Applications (2020).
   DOI: 10.1007/s10589-020-00204-z
9. 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
10. 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
11. 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

Talks

1. ODS 2021 (Rome) – A Unifying Framework for Sparsity Constrained Optimization
2. SIMAI 2020+2021 (Parma) – A Two-Level Decomposition Framework  Exploiting First and Second Order Information for SVM Training  Problems
3. SIAM Conference on Optimization (OP21) – A Penalty Decomposition Approach for Multi-Objective Cardinality-Constrained Optimization Problems.
4. EUROPT 2021 (Toulouse, virtual) – A Derivative-free Adaptation of the Penalty Decomposition Method for Sparse Optimization.
5. ODS 2019 (Genova) – An Efficient Optimization Approach for Subset Selection, with Application to Linear Regression and Auto-Regressive Time Series.

Contacts

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

E-mail: matlapucci at gmail dot com