Some results on statistics and functional data analysis

Abstract

This paper presents some recent results on regression and classification in Functional Data Analysis setting. The first work decated to Multiple kernel SVM for classifying functional data in Sobolev spaces focus on optimization of the information from each derivatives of the original functions, the second work devoted to An input/output-based aggregation rule for functional data classification when the last is interested with the problem of regression if the functional data lives in a finite dimensionnal submanifold.