Stable Discriminative Dictionary Learning via Discriminative Deviation

被引：0

作者：

Khan, Nazar ^{[1
]}

Tappen, Marshall ^{[1
]}

机构：

[1] Univ Cent Florida, Orlando, FL 32816 USA

来源：

2012 21ST INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR 2012) | 2012年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Discriminative learning of sparse-code based dictionaries tends to be inherently unstable. We show that using a discriminative version of the deviation function to learn such dictionaries leads to a more stable formulation that can handle the reconstruction/discrimination trade-off in a principled manner. Results on Graz02 and UCF Sports datasets validate the proposed formulation.

引用

页码：3224 / 3227

页数：4

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