Statistical Learning Theory with applications on Shallow and Deep Learning algorithms

Abstract: This course addresses the main concepts of the Statistical Learning Theory (SLT) and how they are applied to ensure bounds to supervised learning algorithms. Shallow and deep networks will be considered as special cases to illustrate their complexities and learning convergences.