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JMLR
2008
114views more  JMLR 2008»
13 years 9 months ago
Coordinate Descent Method for Large-scale L2-loss Linear Support Vector Machines
Linear support vector machines (SVM) are useful for classifying large-scale sparse data. Problems with sparse features are common in applications such as document classification a...
Kai-Wei Chang, Cho-Jui Hsieh, Chih-Jen Lin
TNN
2008
152views more  TNN 2008»
13 years 8 months ago
Distributed Parallel Support Vector Machines in Strongly Connected Networks
We propose a distributed parallel support vector machine (DPSVM) training mechanism in a configurable network environment for distributed data mining. The basic idea is to exchange...
Yumao Lu, Vwani P. Roychowdhury, L. Vandenberghe
ESWA
2006
102views more  ESWA 2006»
13 years 9 months ago
A study of Taiwan's issuer credit rating systems using support vector machines
By providing credit risk information, credit rating systems benefit most participants in financial markets, including issuers, investors, market regulators and intermediaries. In ...
Wun-Hwa Chen, Jen-Ying Shih
BIBM
2008
IEEE
137views Bioinformatics» more  BIBM 2008»
14 years 3 months ago
Exploring Alternative Splicing Features Using Support Vector Machines
Alternative splicing is a mechanism for generating different gene transcripts (called isoforms) from the same genomic sequence. Finding alternative splicing events experimentally ...
Jing Xia, Doina Caragea, Susan Brown
ACL
2009
13 years 6 months ago
A Novel Discourse Parser Based on Support Vector Machine Classification
This paper introduces a new algorithm to parse discourse within the framework of Rhetorical Structure Theory (RST). Our method is based on recent advances in the field of statisti...
David duVerle, Helmut Prendinger