We propose to study links between three important classification algorithms: Perceptrons, Multi-Layer Perceptrons (MLPs) and Support Vector Machines (SVMs). We first study ways to...
Abstract We propose in this paper a novel approach to the classification of discrete sequences. This approach builds a model fitting some dynamical features deduced from the learni...
In many machine learning applications, like Brain - Computer Interfaces (BCI), only high-dimensional noisy data are available rendering the discrimination task non-trivial. In thi...
Abstract. The support vector machine (SVM) constitutes one of the most successful current learning algorithms with excellent classification accuracy in large real-life problems an...
We propose preprocessing spectral clustering with b-matching to remove spurious edges in the adjacency graph prior to clustering. B-matching is a generalization of traditional maxi...