Theoretically well-founded, Support Vector Machines (SVM)are well-knownto be suited for efficiently solving classification problems. Althoughimprovedgeneralization is the maingoal...
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...
Background: Cancer diagnosis and clinical outcome prediction are among the most important emerging applications of gene expression microarray technology with several molecular sig...
Alexander R. Statnikov, Lily Wang, Constantin F. A...
Support vector machines (SVMs) have proven to be a powerful technique for pattern classification. SVMs map inputs into a high dimensional space and then separate classes with a hy...
William M. Campbell, Joseph P. Campbell, Douglas A...
Practical experience has shown that in order to obtain the best possible performance, prior knowledge about invariances of a classification problem at hand ought to be incorporated...