Constrained Low-Rank Representation for Robust Subspace Clustering

@article{Wang2017ConstrainedLR,
  title={Constrained Low-Rank Representation for Robust Subspace Clustering},
  author={Jing Wang and Xiao Hu Wang and Feng Tian and Chang Hong Liu and Hongchuan Yu},
  journal={IEEE Transactions on Cybernetics},
  year={2017},
  volume={47},
  pages={4534-4546}
}
Subspace clustering aims to partition the data points drawn from a union of subspaces according to their underlying subspaces. For accurate semisupervised subspace clustering, all data that have a must-link constraint or the same label should be grouped into the same underlying subspace. However, this is not guaranteed in existing approaches. Moreover, these approaches require additional parameters for incorporating supervision information. In this paper, we propose a constrained low-rank… CONTINUE READING