We study multi-category classification in the framework of computational learning theory. We show how a relaxation approach, which is commonly used in binary classification, can be generalized to the multi-class setting. ...

In this work we are interested in the problems of supervised learning and variable selection when the input-output dependence is described by a nonlinear function depending on a few variables. Our goal is to consider a ...

In this work we discuss a regularization framework to solve multi-category when the classes are described by an underlying class taxonomy. In particular we discuss how to learn the class taxonomy while learning a multi-category ...