Sparse representation using nonnegative curds and whey

  title={Sparse representation using nonnegative curds and whey},
  author={Yanan Liu and Fei Wu and Zhihua Zhang and Yueting Zhuang and Shuicheng Yan},
  journal={2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition},
It has been of great interest to find sparse and/or nonnegative representations in computer vision literature. In this paper we propose a novel method to such a purpose and refer to it as nonnegative curds and whey (NNCW). The NNCW procedure consists of two stages. In the first stage we consider a set of sparse and nonnegative representations of a test image, each of which is a linear combination of the images within a certain class, by solving a set of regressiontype nonnegative matrix… CONTINUE READING
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Better subset regression using the nonnegative garrote

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