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ML
2002
ACM
107views Machine Learning» more  ML 2002»
14 years 9 months ago
Training Invariant Support Vector Machines
Practical experience has shown that in order to obtain the best possible performance, prior knowledge about invariances of a classification problem at hand ought to be incorporated...
Dennis DeCoste, Bernhard Schölkopf
SYNASC
2006
IEEE
95views Algorithms» more  SYNASC 2006»
15 years 3 months ago
Evolutionary Support Vector Regression Machines
Evolutionary support vector machines (ESVMs) are a novel technique that assimilates the learning engine of the state-of-the-art support vector machines (SVMs) but evolves the coef...
Ruxandra Stoean, Dumitru Dumitrescu, Mike Preuss, ...
AAAI
2006
14 years 11 months ago
Closest Pairs Data Selection for Support Vector Machines
This paper presents data selection procedures for support vector machines (SVM). The purpose of data selection is to reduce the dataset by eliminating as many non support vectors ...
Chaofan Sun
TR
2010
204views Hardware» more  TR 2010»
14 years 4 months ago
Anomaly Detection Through a Bayesian Support Vector Machine
This paper investigates the use of a one-class support vector machine algorithm to detect the onset of system anomalies, and trend output classification probabilities, as a way to ...
Vasilis A. Sotiris, Peter W. Tse, Michael Pecht
KDD
2000
ACM
133views Data Mining» more  KDD 2000»
15 years 1 months ago
Data selection for support vector machine classifiers
The problem of extracting a minimal number of data points from a large dataset, in order to generate a support vector machine (SVM) classifier, is formulated as a concave minimiza...
Glenn Fung, Olvi L. Mangasarian