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» Ellipsoidal Support Vector Machines
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KDD
2006
ACM
165views Data Mining» more  KDD 2006»
16 years 2 months ago
Training linear SVMs in linear time
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...
Thorsten Joachims
ECML
2004
Springer
15 years 7 months ago
Using String Kernels to Identify Famous Performers from Their Playing Style
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...
GECCO
2008
Springer
232views Optimization» more  GECCO 2008»
15 years 3 months ago
An efficient SVM-GA feature selection model for large healthcare databases
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...
BMCBI
2010
98views more  BMCBI 2010»
15 years 2 months ago
Learning to predict expression efficacy of vectors in recombinant protein production
Background: Recombinant protein production is a useful biotechnology to produce a large quantity of highly soluble proteins. Currently, the most widely used production system is t...
Wen-Ching Chan, Po-Huang Liang, Yan-Ping Shih, Uen...
BMCBI
2010
130views more  BMCBI 2010»
15 years 2 months ago
Amino acid "little Big Bang": Representing amino acid substitution matrices as dot products of Euclidian vectors
Background: Sequence comparisons make use of a one-letter representation for amino acids, the necessary quantitative information being supplied by the substitution matrices. This ...
Karel Zimmermann, Jean-François Gibrat