Alessandro Verri

Title:  Regularization Algorithms for Learning

Abstract:

In this talk we investigate the close relationship between learning and regularization by importing in the learning domain algorithms developed in the context of regularization theory. We describe a nonlinear regularization algorithm which seems to be well suited to address the problem of feature selection. We discuss theoretical properties, implementation issues and experimental results in real world problems.