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» Optimization on Support Vector Machines
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ICIP
2000
IEEE
15 years 11 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
15 years 10 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
15 years 10 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
15 years 10 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 3 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