- Emanuele Frandi, Confronto Numerico tra Algoritmi MEB per l’Addestramento di SVM nei Problemi di Classificazione, Master’s Thesis (in Italian), Università degli Studi di Firenze, 2010.
- Emanuele Frandi, Enhancing Direct Search Methods by Multilevel Techniques: Algorithms and Applications, PhD Thesis, Università degli Studi dell’Insubria, 2014.
Papers
- Emanuele Frandi, Maria Grazia Gasparo, Stefano Lodi, Ricardo Nanculef and Claudio Sartori, A new algorithm for training SVMs using approximate minimal enclosing balls, in: Proceedings of the 15th Iberoamerican Congress on Pattern Recognition, Lecture Notes in Computer Science, 6419, 87-95, Springer, 2010.
- Emanuele Frandi, Maria Grazia Gasparo, Ricardo Nanculef and Alessandra Papini, Solution of classification problems via computational geometry methods, Recent Advances in Nonlinear Optimization and Equilibrium Problems: a Tribute to Marco D’Apuzzo, Quaderni di Matematica, 27, 201–226, 2012.
- Emanuele Frandi, Ricardo Nanculef, Maria Grazia Gasparo, Stefano Lodi and Claudio Sartori, Training support vector machines using Frank-Wolfe optimization methods, International Journal of Pattern Recognition and Artificial Intelligence 27(3), 2013.
- Emanuele Frandi and Alessandra Papini, Coordinate search algorithms in multilevel optimization, Optimization Methods and Software 29(5), 1020-1041, 2014.
- Ricardo Nanculef, Emanuele Frandi, Claudio Sartori and Hector Allende, A novel Frank-Wolfe algorithm. Analysis and applications to large-scale SVM training, Information Sciences 285, 66-99, 2014.
- Marco Signoretto, Emanuele Frandi, Zahra Karevan and Johan Suykens, High Level High Performance Computing for Multitask Learning of Time-varying Models, Proceedings of the IEEE Symposium on Computational Intelligence in Big Data (IEEE-CIBD), 2014.
- Emanuele Frandi and Alessandra Papini, Improving direct search algorithms by multilevel optimization techniques, Optimization Methods and Software 30(5), 1077--1094, 2015.
- Emanuele Frandi, Ricardo Nanculef and Johan A. K. Suykens, Complexity issues and randomization strategies in Frank-Wolfe algorithms for Machine Learning, 2014 NIPS Workshop on Optimization for Machine Learning.
- Emanuele Frandi, Ricardo Nanculef and Johan A. K. Suykens, A PARTAN-accelerated Frank-Wolfe algorithm for large-scale SVM classification, Proceedings of the International Joint Conference on Neural Networks (IJCNN), 2015.
- Emanuele Frandi, Ricardo Nanculef, Stefano Lodi, Claudio Sartori and Johan A. K. Suykens, Fast and Scalable Lasso via Stochastic Frank-Wolfe Methods with a Convergence Guarantee, Machine Learning 104(2), 195-221, 2016.