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» Large Scale Transductive SVMs
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NIPS
2004
13 years 9 months ago
Parallel Support Vector Machines: The Cascade SVM
We describe an algorithm for support vector machines (SVM) that can be parallelized efficiently and scales to very large problems with hundreds of thousands of training vectors. I...
Hans Peter Graf, Eric Cosatto, Léon Bottou,...
BMCBI
2005
97views more  BMCBI 2005»
13 years 7 months ago
The yeast kinome displays scale free topology with functional hub clusters
Background: The availability of interaction databases provides an opportunity for researchers to utilize immense amounts of data exclusively in silico. Recently there has been an ...
Robin E. C. Lee, Lynn A. Megeney
KDD
2006
ACM
201views Data Mining» more  KDD 2006»
14 years 8 months ago
Clustering based large margin classification: a scalable approach using SOCP formulation
This paper presents a novel Second Order Cone Programming (SOCP) formulation for large scale binary classification tasks. Assuming that the class conditional densities are mixture...
J. Saketha Nath, Chiranjib Bhattacharyya, M. Naras...
ICPR
2006
IEEE
14 years 9 months ago
Mixture of Support Vector Machines for HMM based Speech Recognition
Speech recognition is usually based on Hidden Markov Models (HMMs), which represent the temporal dynamics of speech very efficiently, and Gaussian mixture models, which do non-opt...
Sven E. Krüger, Martin Schafföner, Marce...
TNN
2008
97views more  TNN 2008»
13 years 7 months ago
Training Hard-Margin Support Vector Machines Using Greedy Stagewise Algorithm
Hard-margin support vector machines (HM-SVMs) suffer from getting overfitting in the presence of noise. Soft-margin SVMs deal with this problem by introducing a regularization term...
Liefeng Bo, Ling Wang, Licheng Jiao