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ICML
2006
IEEE
14 years 8 months ago
Two-dimensional solution path for support vector regression
Recently, a very appealing approach was proposed to compute the entire solution path for support vector classification (SVC) with very low extra computational cost. This approach ...
Gang Wang, Dit-Yan Yeung, Frederick H. Lochovsky
UAI
2000
13 years 9 months ago
Variational Relevance Vector Machines
The Support Vector Machine (SVM) of Vapnik [9] has become widely established as one of the leading approaches to pattern recognition and machine learning. It expresses predictions...
Christopher M. Bishop, Michael E. Tipping
JMLR
2008
133views more  JMLR 2008»
13 years 7 months ago
Algorithms for Sparse Linear Classifiers in the Massive Data Setting
Classifiers favoring sparse solutions, such as support vector machines, relevance vector machines, LASSO-regression based classifiers, etc., provide competitive methods for classi...
Suhrid Balakrishnan, David Madigan
ICML
2005
IEEE
14 years 8 months ago
Core Vector Regression for very large regression problems
In this paper, we extend the recently proposed Core Vector Machine algorithm to the regression setting by generalizing the underlying minimum enclosing ball problem. The resultant...
Ivor W. Tsang, James T. Kwok, Kimo T. Lai
BMCBI
2008
165views more  BMCBI 2008»
13 years 7 months ago
Peak intensity prediction in MALDI-TOF mass spectrometry: A machine learning study to support quantitative proteomics
Background: Mass spectrometry is a key technique in proteomics and can be used to analyze complex samples quickly. One key problem with the mass spectrometric analysis of peptides...
Wiebke Timm, Alexandra Scherbart, Sebastian Bö...