My research interests are machine learning, optimization applications and other topics related to them. In particular, my principal addressed problems are protein folding, anomaly detection and clustering.
- Pareto Front Approximation through a Multi-objective Augmented Lagrangian Method.
G. Cocchi, M. Lapucci, P. Mansueto.
EURO Journal on Computational Optimization (2021).
- Memetic differential evolution methods for clustering problems.
P. Mansueto, F. Schoen.
Pattern Recognition (2021).
- Recognition of Concordances for Indexing in Digital Libraries.
S. Marinai, S. Capobianco, Z. Ziran, A. Giuntini, P. Mansueto.
Digital Libraries: The Era of Big Data and Data Science (2020).
My ORCID number: 0000-0002-1394-0937.
- EUROPT 2021, Toulouse (virtual) — Pareto Front Approximation through a Multi-objective Augmented Lagrangian Method
- ODS 2021, Rome — Improving the NSGA-II Algorithm with Descent Steps
E-mails: pierluigi dot mansueto at unifi dot it, pierluigimansueto at gmail dot com