We extend Support Vector Machines to input spaces that are sets by ensuring that the classifier is invariant to permutations of subelements within each input. Such permutations in...
Linear Support Vector Machines (SVMs) have become one of the most prominent machine learning techniques for highdimensional sparse data commonly encountered in applications like t...
Large numbers of logical registers can improve performance by allowing fast access to multiple subroutine contexts (register windows) and multiple thread contexts (multithreading)...
David W. Oehmke, Nathan L. Binkert, Trevor N. Mudg...
Abstract. In this paper we show a novel application of string kernels: that is to the problem of recognising famous pianists from their style of playing. The characterstics of perf...
Craig Saunders, David R. Hardoon, John Shawe-Taylo...
This paper presents an efficient hybrid feature selection model based on Support Vector Machine (SVM) and Genetic Algorithm (GA) for large healthcare databases. Even though SVM an...
Rick Chow, Wei Zhong, Michael Blackmon, Richard St...