Contents Special Issue: Recent Trend in Computational Method

@inproceedings{Gao2011ContentsSI,
  title={Contents Special Issue: Recent Trend in Computational Method},
  author={Feng Gao and Tokuro Matsuo and Junhu Zhang and Shifei Ding},
  year={2011}
}
Support vector data description (SVDD) has become a very attractive kernel method due to its good results in many novelty detection problems.Training SVDD involves solving a constrained convex quadratic programming,which requires large memory and enormous amounts of training time for large-scale data set.In this paper,we analyze the possible changes of support vector set after new samples are added to training set according to the relationship between the Karush-Kuhn-Tucker (KKT) conditions of… CONTINUE READING

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