Non-Intrusive Load Monitoring with an Attention-based Deep Neural Network. - Antonio Maria Sudoso; Veronica Piccialli (CoRR, 2019)

A machine learning approach for forecasting hierarchical time series. - Paolo Mancuso; Veronica Piccialli; Antonio Maria Sudoso (Expert Syst. Appl., 2021)

An exact algorithm for semi-supervised minimum sum-of-squares clustering. - Veronica Piccialli; Anna Russo Russo; Antonio Maria Sudoso (Comput. Oper. Res., 2022)

SOS-SDP: An Exact Solver for Minimum Sum-of-Squares Clustering. - Veronica Piccialli; Antonio Maria Sudoso; Angelika Wiegele (INFORMS J. Comput., 2022)

Mixed-Integer Nonlinear Programming for State-Based Non-Intrusive Load Monitoring. - Marco Balletti; Veronica Piccialli; Antonio Maria Sudoso (IEEE Trans. Smart Grid, 2022)

Predicting municipalities in financial distress: a machine learning approach enhanced by domain expertise. - Dario Piermarini; Antonio Maria Sudoso; Veronica Piccialli (CoRR, 2023)

Multi-task learning of convex combinations of forecasting models. - Giovanni Felici; Antonio Maria Sudoso (CoRR, 2023)

Optimization meets Machine Learning: An Exact Algorithm for Semi-Supervised Support Vector Machines. - Veronica Piccialli; Jan Schwiddessen; Antonio Maria Sudoso (CoRR, 2023)

An SDP-based Branch-and-Cut Algorithm for Biclustering. - Antonio Maria Sudoso (CoRR, 2024)

A column generation algorithm with dynamic constraint aggregation for minimum sum-of-squares clustering. - Antonio Maria Sudoso; Daniel Aloise (CoRR, 2024)

Strong bounds for large-scale Minimum Sum-of-Squares Clustering. - Anna Livia Croella; Veronica Piccialli; Antonio Maria Sudoso (CoRR, 2025)

Global optimization for cardinality-constrained minimum sum-of-squares clustering via semidefinite programming. - Veronica Piccialli; Antonio Maria Sudoso (Math. Program., 2025)

Fix and bound: an efficient approach for solving large-scale quadratic programming problems with box constraints. - Marco Locatelli 001; Veronica Piccialli; Antonio Maria Sudoso (Math. Program. Comput., 2025)