The standard SVM formulation for binary classification is based on the Hinge loss function, where errors are considered not correlated. Due to this, local information in the featu...
In this paper we describe work on the automatic recognition of island structures. In an initial phase several test persons were asked to mark groups of islands that they perceived...
We study a generalized framework for structured sparsity. It extends the well known methods of Lasso and Group Lasso by incorporating additional constraints on the variables as pa...
Luca Baldassarre, Jean Morales, Andreas Argyriou, ...
Linear Discriminant Analysis (LDA) is one of the wellknown methods for supervised dimensionality reduction. Over the years, many LDA-based algorithms have been developed to cope w...
This paper proposes the use of constructive ordinals as mistake bounds in the on-line learning model. This approach elegantly generalizes the applicability of the on-line mistake ...