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NIPS
1996
13 years 9 months ago
Improving the Accuracy and Speed of Support Vector Machines
Support Vector Learning Machines (SVM) are nding application in pattern recognition, regression estimation, and operator inversion for ill-posed problems. Against this very genera...
Christopher J. C. Burges, Bernhard Schölkopf
ICML
2006
IEEE
14 years 1 months ago
Multiclass reduced-set support vector machines
There are well-established methods for reducing the number of support vectors in a trained binary support vector machine, often with minimal impact on accuracy. We show how reduce...
Benyang Tang, Dominic Mazzoni
ICDM
2002
IEEE
133views Data Mining» more  ICDM 2002»
14 years 21 days ago
Learning with Progressive Transductive Support Vector Machine
Support vector machine (SVM) is a new learning method developed in recent years based on the foundations of statistical learning theory. By taking a transductive approach instead ...
Yisong Chen, Guoping Wang, Shihai Dong
ISCAS
2005
IEEE
142views Hardware» more  ISCAS 2005»
14 years 1 months ago
Hardware-based support vector machine classification in logarithmic number systems
—Support Vector Machines are emerging as a powerful machine-learning tool. Logarithmic Number Systems (LNS) utilize the property of logarithmic compression for numerical operatio...
Faisal M. Khan, Mark G. Arnold, William M. Potteng...
MICCAI
2006
Springer
14 years 8 months ago
The Entire Regularization Path for the Support Vector Domain Description
Abstract. The support vector domain description is a one-class classification method that estimates the shape and extent of the distribution of a data set. This separates the data ...
Karl Sjöstrand, Rasmus Larsen