RES-PCA: A Scalable Approach to Recovering Low-Rank Matrices

Chong Peng, Chenglizhao Chen, Zhao Kang, Jianbo Li, Qiang Cheng. RES-PCA: A Scalable Approach to Recovering Low-Rank Matrices. In IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2019, Long Beach, CA, USA, June 16-20, 2019. pages 7317-7325, Computer Vision Foundation / IEEE, 2019. [doi]

@inproceedings{PengCKLC19,
  title = {RES-PCA: A Scalable Approach to Recovering Low-Rank Matrices},
  author = {Chong Peng and Chenglizhao Chen and Zhao Kang and Jianbo Li and Qiang Cheng},
  year = {2019},
  url = {http://openaccess.thecvf.com/content_CVPR_2019/html/Peng_RES-PCA_A_Scalable_Approach_to_Recovering_Low-Rank_Matrices_CVPR_2019_paper.html},
  researchr = {https://researchr.org/publication/PengCKLC19},
  cites = {0},
  citedby = {0},
  pages = {7317-7325},
  booktitle = {IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2019, Long Beach, CA, USA, June 16-20, 2019},
  publisher = {Computer Vision Foundation / IEEE},
}