2022
Functional Output Regression with Infimal Convolution: Exploring the Huber and $ε$-insensitive Losses
ICML 2022spotlight
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 $\epsilon$-insensitive loss (induced by infimal convolution) and propose a flexible framework capable of handlin…