NODA - Numerical Optimization and Data Analysis
Scientific coordinator: Prof. Stefano Bellavia
The group studies numerical methods for solving large-scale continuous optimization problems with and without constraints on variables, including methods for problems arising in the field of machine learning. The objectives of the activity are: the definition of innovative algorithms and the creation of robust, reliable, and well-documented numerical software for complex problems arising in different application areas.
Last update
03.03.2026