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» Learning with Rigorous Support Vector Machines
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TKDE
2008
123views more  TKDE 2008»
15 years 3 months ago
Explaining Classifications For Individual Instances
We present a method for explaining predictions for individual instances. The presented approach is general and can be used with all classification models that output probabilities...
Marko Robnik-Sikonja, Igor Kononenko
ICONIP
2007
15 years 5 months ago
Using Generalization Error Bounds to Train the Set Covering Machine
In this paper we eliminate the need for parameter estimation associated with the set covering machine (SCM) by directly minimizing generalization error bounds. Firstly, we consider...
Zakria Hussain, John Shawe-Taylor
PR
2008
91views more  PR 2008»
15 years 3 months ago
Applying the multi-category learning to multiple video object extraction
Video object (VO) extraction is of great importance in multimedia processing. In recent years approaches have been proposed to deal with VO extraction as a classification problem....
Yi Liu, Yuan F. Zheng, Xiaotong Shen
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...
ICC
2007
IEEE
141views Communications» more  ICC 2007»
15 years 10 months ago
Accurate Classification of the Internet Traffic Based on the SVM Method
—The need to quickly and accurately classify Internet traffic for security and QoS control has been increasing significantly with the growing Internet traffic and applications ov...
Zhu Li, Ruixi Yuan, Xiaohong Guan