Fast support vector data descriptions for novelty detection

IEEE Transactions on Neural Networks
Yi-Hung LiuYen-Jen Chen

Abstract

Support vector data description (SVDD) has become a very attractive kernel method due to its good results in many novelty detection problems. However, the decision function of SVDD is expressed in terms of the kernel expansion, which results in a run-time complexity linear in the number of support vectors. For applications where fast real-time response is needed, how to speed up the decision function is crucial. This paper aims at dealing with the issue of reducing the testing time complexity of SVDD. A method called fast SVDD (F-SVDD) is proposed. Unlike the traditional methods which all try to compress a kernel expansion into one with fewer terms, the proposed F-SVDD directly finds the preimage of a feature vector, and then uses a simple relationship between this feature vector and the SVDD sphere center to re-express the center with a single vector. The decision function of F-SVDD contains only one kernel term, and thus the decision boundary of F-SVDD is only spherical in the original space. Hence, the run-time complexity of the F-SVDD decision function is no longer linear in the support vectors, but is a constant, no matter how large the training set size is. In this paper, we also propose a novel direct preimage-finding me...Continue Reading

References

Oct 14, 2000·Neural Computation·G Baudat, F Anouar
Jul 7, 2001·Neural Computation·B SchölkopfR C Williamson
Nov 30, 2004·IEEE Transactions on Neural Networks·James Tin-yau Kwok, Ivor Wai-hung Tsang
Jun 9, 2005·IEEE Transactions on Neural Networks·Norikazu Takahashi, Tetsuo Nishi
Dec 14, 2005·IEEE Transactions on Neural Networks·Qing TaoJue Wang
Sep 28, 2006·IEEE Transactions on Neural Networks·Ivor Wai-Hung TsangJacek M Zurada
Feb 7, 2007·IEEE Transactions on Neural Networks·Yi-Hung Liu, Yen-Ting Chen
Feb 7, 2007·IEEE Transactions on Neural Networks·Kiyoung LeeDoheon Lee
May 25, 2007·Neural Computation·Jooyoung ParkIvor W Tsang
Feb 2, 2008·IEEE Transactions on Neural Networks·Juwei LuA N Venetsanopoulos
Feb 6, 2008·IEEE Transactions on Neural Networks·A Navia-VázquezA R Figueiras-Vidal
Feb 7, 2008·IEEE Transactions on Neural Networks·B SchölkopfA J Smola

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Citations

May 16, 2012·Journal of Chemical Information and Modeling·Alexandre Varnek, Igor Baskin
Oct 22, 2011·International Journal of Molecular Sciences·Yi-Hung Liu, Yan-Jen Chen
Jul 17, 2014·IEEE Transactions on Neural Networks and Learning Systems·Yuichi Motai
Feb 27, 2015·IEEE Transactions on Neural Networks and Learning Systems·Xuemei DingLiam P Maguire
Dec 23, 2014·IEEE Transactions on Neural Networks and Learning Systems·Yongqiao WangShouyang Wang
Feb 10, 2017·Computational Intelligence and Neuroscience·Erik MarchiBjörn Schuller

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