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» Robust feature induction for support vector machines
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ML
2010
ACM
181views Machine Learning» more  ML 2010»
14 years 8 months ago
Decomposing the tensor kernel support vector machine for neuroscience data with structured labels
Abstract The tensor kernel has been used across the machine learning literature for a number of purposes and applications, due to its ability to incorporate samples from multiple s...
David R. Hardoon, John Shawe-Taylor
BIBE
2003
IEEE
124views Bioinformatics» more  BIBE 2003»
15 years 3 months ago
Prediction of Contact Maps Using Support Vector Machines
Contact map prediction is of great interest for its application in fold recognition and protein 3D structure determination. In this paper we present a contact-map prediction algor...
Ying Zhao, George Karypis
IJCNN
2006
IEEE
15 years 3 months ago
Learning the Kernel in Mahalanobis One-Class Support Vector Machines
— In this paper, we show that one-class SVMs can also utilize data covariance in a robust manner to improve performance. Furthermore, by constraining the desired kernel function ...
Ivor W. Tsang, James T. Kwok, Shutao Li
ACIVS
2005
Springer
15 years 3 months ago
Gender Classification in Human Gait Using Support Vector Machine
We describe an automated system that classifies gender by utilising a set of human gait data. The gender classification system consists of three stages: i) detection and extraction...
Jang-Hee Yoo, Doosung Hwang, Mark S. Nixon
BMCBI
2010
151views more  BMCBI 2010»
14 years 9 months ago
Classification of G-protein coupled receptors based on support vector machine with maximum relevance minimum redundancy and gene
Background: Because a priori knowledge about function of G protein-coupled receptors (GPCRs) can provide useful information to pharmaceutical research, the determination of their ...
Zhanchao Li, Xuan Zhou, Zong Dai, Xiaoyong Zou