PALAGI, LAURA
PALAGI, LAURA
Block layer decomposition schemes for training deep neural networks
2020 Palagi, Laura; Seccia, Ruggiero
Branching with hyperplanes in the criterion space: The frontier partitioner algorithm for biobjective integer programming
2020 De Santis, Marianna; Grani, Giorgio; Palagi, Laura
Considering patient clinical history impacts performance of machine learning models in predicting course of multiple sclerosis
2020 Seccia, R.; Gammelli, D.; Dominici, F.; Romano, S.; Landi, A. C.; Salvetti, M.; Tacchella, A.; Zaccaria, A.; Crisanti, A.; Grassi, F.; Palagi, L.
Data of patients undergoing rehabilitation programs
2020 Seccia, Ruggiero; Boresta, Marco; Fusco, Federico; Tronci, Edoardo; Di Gemma, Emanuele; Palagi, Laura; Mangone, Massimiliano; Agostini, Francesco; Bernetti, Andrea; Santilli, Valter; Damiani, Carlo; Goffredo, Michela; Franceschini, Marco
A neural network approach to the combined multi-objective optimization of the thermodynamic cycle and the radial inflow turbine for Organic Rankine cycle applications
2019 Palagi, Laura; Sciubba, Enrico; Tocci, Lorenzo
Global optimization issues in deep network regression: an overview
2019 Palagi; Laura
A truncated Newton method in an augmented Lagrangian framework for nonlinear programming
2010 Di Pillo, G.; Liuzzi, G.; Lucidi, S.; Palagi, L.
A convergent decomposition algorithm for support vector machines
2007 Lucidi, S; Palagi, L; Risi, A; Sciandrone, M
Convergence to 2nd order stationary points of a primal-dual algorithm model for nonlinear programming
2005 Di Pillo, G; Lucidi, S; Palagi, L
On the convergence of a modified version of the SVMlight algorithm
2005 Palagi, L; Sciandrone, M
Quartic formulation of standard quadratic optimization
2005 Bomze, I; Palagi, L
A Truncated Newton Algorithm for Large Scale Box Constrained Optimization
2002 Facchinei, F.; Lucidi, S.; Palagi, L.