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» Optimization on Support Vector Machines
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ICML
2004
IEEE
15 years 10 months ago
Multiple kernel learning, conic duality, and the SMO algorithm
While classical kernel-based classifiers are based on a single kernel, in practice it is often desirable to base classifiers on combinations of multiple kernels. Lanckriet et al. ...
Francis R. Bach, Gert R. G. Lanckriet, Michael I. ...
PPOPP
2009
ACM
15 years 10 months ago
Mapping parallelism to multi-cores: a machine learning based approach
The efficient mapping of program parallelism to multi-core processors is highly dependent on the underlying architecture. This paper proposes a portable and automatic compiler-bas...
Zheng Wang, Michael F. P. O'Boyle
ISF
2010
164views more  ISF 2010»
14 years 7 months ago
An SVM-based machine learning method for accurate internet traffic classification
Accurate and timely traffic classification is critical in network security monitoring and traffic engineering. Traditional methods based on port numbers and protocols have proven t...
Ruixi Yuan, Zhu Li, Xiaohong Guan, Li Xu
NN
2007
Springer
106views Neural Networks» more  NN 2007»
14 years 9 months ago
Machine learning approach to color constancy
A number of machine learning (ML) techniques have recently been proposed to solve color constancy problem in computer vision. Neural networks (NNs) and support vector regression (...
Vivek Agarwal, Andrei V. Gribok, Mongi A. Abidi
CIVR
2008
Springer
245views Image Analysis» more  CIVR 2008»
14 years 11 months ago
Probabilistic optimized ranking for multimedia semantic concept detection via RVM
We present a probabilistic ranking-driven classifier for the detection of video semantic concept, such as airplane, building, etc. Most existing concept detection systems utilize ...
Yantao Zheng, Shi-Yong Neo, Tat-Seng Chua, Qi Tian