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» Support Vector Machines: Theory and Applications
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AUSDM
2006
Springer
177views Data Mining» more  AUSDM 2006»
14 years 5 days ago
On The Optimal Working Set Size in Serial and Parallel Support Vector Machine Learning With The Decomposition Algorithm
The support vector machine (SVM) is a wellestablished and accurate supervised learning method for the classification of data in various application fields. The statistical learnin...
Tatjana Eitrich, Bruno Lang
ML
2007
ACM
130views Machine Learning» more  ML 2007»
13 years 8 months ago
A note on Platt's probabilistic outputs for support vector machines
Platt’s probabilistic outputs for Support Vector Machines (Platt, 2000) has been popular for applications that require posterior class probabilities. In this note, we propose an ...
Hsuan-Tien Lin, Chih-Jen Lin, Ruby C. Weng
NIPS
1998
13 years 9 months ago
Semi-Supervised Support Vector Machines
We introduce a semi-supervised support vector machine (S3 VM) method. Given a training set of labeled data and a working set of unlabeled data, S3 VM constructs a support vector m...
Kristin P. Bennett, Ayhan Demiriz
DICTA
2003
13 years 9 months ago
Algebraic Curve Fitting Support Vector Machines
An algebraic curve is defined as the zero set of a multivariate polynomial. We consider the problem of fitting an algebraic curve to a set of vectors given an additional set of v...
Christian J. Walder, Brian C. Lovell, Peter J. Koo...
CIKM
2004
Springer
14 years 1 months ago
Hierarchical document categorization with support vector machines
Automatically categorizing documents into pre-defined topic hierarchies or taxonomies is a crucial step in knowledge and content management. Standard machine learning techniques ...
Lijuan Cai, Thomas Hofmann