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» Optimization on Support Vector Machines
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ICIP
2000
IEEE
16 years 4 months ago
Dynamic Memory Model Based Optimization of Scalar and Vector Quantizer for Fast Image Encoding
The rapid progress of computers and today's heterogeneous computing environment means computation-intensive signal processing algorithms must be optimized for performance in ...
Gene Cheung, Steven McCanne
ICML
2006
IEEE
16 years 4 months ago
A continuation method for semi-supervised SVMs
Semi-Supervised Support Vector Machines (S3 VMs) are an appealing method for using unlabeled data in classification: their objective function favors decision boundaries which do n...
Olivier Chapelle, Mingmin Chi, Alexander Zien
DCC
2009
IEEE
16 years 3 months ago
Compressed Kernel Perceptrons
Kernel machines are a popular class of machine learning algorithms that achieve state of the art accuracies on many real-life classification problems. Kernel perceptrons are among...
Slobodan Vucetic, Vladimir Coric, Zhuang Wang
ICML
2003
IEEE
16 years 4 months ago
SimpleSVM
We present a fast iterative support vector training algorithm for a large variety of different formulations. It works by incrementally changing a candidate support vector set usin...
S. V. N. Vishwanathan, Alex J. Smola, M. Narasimha...
ICMCS
2005
IEEE
148views Multimedia» more  ICMCS 2005»
15 years 8 months ago
Facial Expression Recognition with Relevance Vector Machines
For many decades automatic facial expression recognition has scientifically been considered a real challenging problem in the fields of pattern recognition or robotic vision. The ...
Dragos Datcu, Léon J. M. Rothkrantz