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ICDM
2005
IEEE
135views Data Mining» more  ICDM 2005»
15 years 3 months ago
Bit Reduction Support Vector Machine
Abstract— Support vector machines are very accurate classifiers and have been widely used in many applications. However, the training and to a lesser extent prediction time of s...
Tong Luo, Lawrence O. Hall, Dmitry B. Goldgof, And...
NIPS
1996
14 years 11 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
IJCNN
2000
IEEE
15 years 2 months ago
Support Vector Machines Based on a Semantic Kernel for Text Categorization
We propose to solve a text categorization task using a new metric between documents, based on a priori semantic knowledge about words. This metric can be incorporated into the def...
George Siolas, Florence d'Alché-Buc
ECML
2006
Springer
14 years 11 months ago
Efficient Large Scale Linear Programming Support Vector Machines
This paper presents a decomposition method for efficiently constructing 1-norm Support Vector Machines (SVMs). The decomposition algorithm introduced in this paper possesses many d...
Suvrit Sra
ICDM
2008
IEEE
99views Data Mining» more  ICDM 2008»
15 years 4 months ago
Kernels for the Investigation of Localized Spatiotemporal Transitions of Drought with Support Vector Machines
We present and discuss several spatiotemporal kernels designed to mine real-life and simulated data in support of drought prediction. We implement and empirically validate these k...
Matthew W. Collier, Amy McGovern