Functional Output Regression with Infimal Convolution: Exploring the Huber and ε-insensitive Losses

Alex Lambert, Dimitri Bouche, Zoltán Szabó, Florence d'Alché-Buc

Abstract: The focus of the paper is functional output regression (FOR) with convoluted losses. While most existing work consider the square loss setting, we leverage extensions of the Huber and the $\epsilon...