The aim of this paper is to present a dissimilarity measure strategy by which a new philosophy for pattern classification pertaining to dissimilaritybased classifications (DBCs) ca...
The paper deals with the concept of relevance learning in learning vector quantization and classification. Recent machine learning approaches with the ability of metric adaptation...
Thomas Villmann, Frank-Michael Schleif, Barbara Ha...
This paper presents a method to speed up support vector classification, especially important when data is highdimensional. Unlike previous approaches which focus on less support v...
In order to transmit or store three-dimensional (3-D) mesh models efficiently, we need to simplify them. Although the quadric error metric (QEM) provides fast and accurate geometr...
Background: Similarity of sequences is a key mathematical notion for Classification and Phylogenetic studies in Biology. It is currently primarily handled using alignments. Howeve...
Paolo Ferragina, Raffaele Giancarlo, Valentina Gre...