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2012 IEEE 12th International Conference on Data Mining Workshops
Anomalous Neighborhood Selection
Brussels, Belgium Belgium
December 10-December 10
ISBN: 978-1-4673-5164-5
We propose a method to extract row/column-wise heterogeneous elements between two precision matrices for an anomaly localization. We formulate the task as a convex optimization problem using a regularization term that penalizes row/column-wise differences between two matrices. The fundamental difficulties of the problem are that the proposed regularization term (1) is a sum of group-wise regularizations with overlapping supports between the groups, (2) penalizes matrices in a symmetric manner. Our proposed algorithm with an alternating direction method of multipliers can deal with these two difficulties efficiently resulting in a very simple formulation with each updating step computed analytically. We also show the validity of the proposed method through an anomaly localization simulation using a real world data.
Index Terms:
Conferences,Data mining,alternating direction method of multipliers,anomaly localization,precision matrix,graphical Gaussian model
Citation:
Satoshi Hara, Takashi Washio, "Anomalous Neighborhood Selection," icdmw, pp.474-480, 2012 IEEE 12th International Conference on Data Mining Workshops, 2012
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