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ECML
2006
Springer
13 years 9 months ago
Efficient Large Scale Linear Programming Support Vector Machines
This paper presents a decomposition method for efficiently constructing 1-norm Support Vector Machines (SVMs). The decomposition algorithm introduced in this paper possesses many d...
Suvrit Sra
BMCBI
2010
208views more  BMCBI 2010»
13 years 7 months ago
Using machine learning to speed up manual image annotation: application to a 3D imaging protocol for measuring single cell gene
Background: Image analysis is an essential component in many biological experiments that study gene expression, cell cycle progression, and protein localization. A protocol for tr...
Zafer Aydin, John I. Murray, Robert H. Waterston, ...
ICML
2007
IEEE
14 years 8 months ago
Hybrid huberized support vector machines for microarray classification
The large number of genes and the relatively small number of samples are typical characteristics for microarray data. These characteristics pose challenges for both sample classif...
Li Wang, Ji Zhu, Hui Zou
SIGIR
2003
ACM
14 years 28 days ago
Question classification using support vector machines
Question classification is very important for question answering. This paper presents our research work on automatic question classification through machine learning approaches. W...
Dell Zhang, Wee Sun Lee
ALT
2000
Springer
14 years 4 months ago
On the Noise Model of Support Vector Machines Regression
Abstract. Support Vector Machines Regression (SVMR) is a learning technique where the goodness of fit is measured not by the usual quadratic loss function (the mean square error),...
Massimiliano Pontil, Sayan Mukherjee, Federico Gir...