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» Entropy Numbers, Operators and Support Vector Kernels
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SDM
2009
SIAM
161views Data Mining» more  SDM 2009»
14 years 4 months ago
Feature Weighted SVMs Using Receiver Operating Characteristics.
Support Vector Machines (SVMs) are a leading tool in classification and pattern recognition and the kernel function is one of its most important components. This function is used...
Shaoyi Zhang, M. Maruf Hossain, Md. Rafiul Hassan,...
ICML
2006
IEEE
14 years 8 months ago
Nonstationary kernel combination
The power and popularity of kernel methods stem in part from their ability to handle diverse forms of structured inputs, including vectors, graphs and strings. Recently, several m...
Darrin P. Lewis, Tony Jebara, William Stafford Nob...
ESANN
2004
13 years 9 months ago
Using classification to determine the number of finger strokes on a multi-touch tactile device
On certain types of multi-touch touchpads, determining the number of finger stroke is a non-trivial problem. We investigate the application of several classification algorithms to ...
Caspar von Wrede, Pavel Laskov
NOSSDAV
1991
Springer
13 years 11 months ago
Kernel Support for Live Digital Audio and Video
: We have developed a real-time operating system kernel which has been used to support the transmission and reception of streams of live digital audio and video in real-time as par...
Kevin Jeffay, Donald L. Stone, F. Donelson Smith
ICIP
2009
IEEE
13 years 5 months ago
Efficient reduction of support vectors in kernel-based methods
Kernel-based methods, e.g., support vector machine (SVM), produce high classification performances. However, the computation becomes time-consuming as the number of the vectors su...
Takumi Kobayashi, Nobuyuki Otsu