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Learning Theory and Algorithms

Faculty: Ernesto De Vito, Lorenzo Rosasco, Alessandro Verri

Description: We focus on the mathematical aspects of Learning Theory to the purpose of developing algorithms which can effectively learn the solution to a given problem from small samples. Our approach is based on the theory of regularization of ill-posed inverse problems and uses methods from functional analysis, convex analysis, and non-parametric statistics.

We are investigating:




Selected Publications