Similarity-based Classification: Concepts and Algorithms
Y. Chen, E. K. Garcia, M. R. Gupta, A. Rahimi and L. Cazzanti,
JMLR
2009
Added: Monday, April 06, 2009 by Yihua Chen - University of Washington
Tags:
classification, learning, similarity
Kernel-based data fusion and its application to protein function predi...
G. R. G. Lanckriet, M. Deng, N. Cristianini, M. I. Jordan, and W. S. Noble,
Pacific Symposium on Biocomputing
2004
Added: Tuesday, March 10, 2009 by Yihua Chen - University of Washington
Tags:
Classification, MultipleKernelLearning, SVM
An SMO Algorithm for the Potential Support Vector Machine
T. Knebel, S. Hochreiter and K. Obermayer,
Neural Computation
2008
Added: Monday, December 29, 2008 by Yihua Chen - University of Washington
Tags:
Learning, SVM, Classification
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URL
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http://neco.mitpress.org/cgi/content/abstract/20/1/271
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bibtex
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@ARTICLE{Knebel08,
author = {Tilman Knebel and Sepp Hochreiter and Klaus Obermayer},
title = {An {SMO} Algorithm for the Potential Support Vector Machine},
journal = {Neural Computation},
year = {2008},
volume = {20},
pages = {271--287},
number = {1},
month = {January}
}
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Comments
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No Comments.
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Support Vector Machines for Dyadic Data
S. Hochreiter and K. Obermayer,
Neural Computation
2006
Added: Monday, December 29, 2008 by Yihua Chen - University of Washington
Tags:
Learning, SVM, Classification
Learning Similarity with Operator-valued Large-margin Classifiers
A. Maurer,
JMLR
2008
Added: Friday, January 23, 2009 by Andreas Maurer - none
Tags:
Classification, Learning, Similarity