Kernel classifiers based on Support Vector Machines (SVM) have recently achieved state-of-the art results on several popular datasets like Caltech or Pascal. This was possible by...
In this paper we present preliminary results stemming from a novel application of Markov Models and Support Vector Machines to splice site classification of Intron-Exon and Exon-I...
Support Vector Machines (SVMs) for classification tasks produce sparse models by maximizing the margin. Two limitations of this technique are considered in this work: firstly, th...
— We discuss sparse support vector machines (sparse SVMs) trained in the reduced empirical feature space. Namely, we select the linearly independent training data by the Cholesky...
This paper proposes a learning and extracting method of word sequence correspondences from non-aligned parallel corpora with Support Vector Machines, which have high ability of th...