DescriptionIn many practical problems, it is convenient to model the object of interest as a function with multiple outputs. In machine learning, this problem typically goes under the name of multi-task or multi-output learning. We present some concepts and algorithms to solve these kinds of problems using kernel methods and regularization.
SlidesSlides for this lecture: PDF
T. Evgeniou and C.A. Micchelli and M. Pontil Learning multiple tasks with kernel methods
M. Pontil and C.A. Micchelli. Kernels for multi-task learning
M. Pontil and C.A. Micchelli. On learning vector-valued functions