The Computational mathematics for learning and data analysis exam’s project consists of:
The problem of estimating the matrix norm-2 of A for a (possibly rectangular) matrix, using its definition as an (unconstrained) maximum problem. Using:
- A standard gradient descent (steepest descent) approach.
- A quasi-Newton method such as BFGS.
Skills acquired:
- Using MATLAB
- Implementing from scratch optimization algorithm in Python
Team members:
- Michele Morisco
- Margherita Pensa
Michele Morisco
MSc in Artificial Intelligence | Lead Programmer at GlaringBit games | Programmer at B.K. - Brain and Knowledge
My academic interests include Deep Learning, Machine Learning, Computational Healthcare and 3D geometric processing.