ML Anthology

R1-PCA: Rotational Invariant L1-Norm Principal Component Analysis for Robust Subspace Factorization

Chris H. Q. Ding, Ding Zhou, Xiaofeng He, Hongyuan Zha
ICML 2006 pp. 281-288
doi:10.1145/1143844.1143880 /icml/2006/ding2006icml-r/
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Cite

Text

Ding et al. "R1-PCA: Rotational Invariant L1-Norm Principal Component Analysis for Robust Subspace Factorization." International Conference on Machine Learning, 2006. doi:10.1145/1143844.1143880

Markdown

[Ding et al. "R1-PCA: Rotational Invariant L1-Norm Principal Component Analysis for Robust Subspace Factorization." International Conference on Machine Learning, 2006.](https://mlanthology.org/icml/2006/ding2006icml-r/) doi:10.1145/1143844.1143880

BibTeX

@inproceedings{ding2006icml-r,
  title     = {{R1-PCA: Rotational Invariant L1-Norm Principal Component Analysis for Robust Subspace Factorization}},
  author    = {Ding, Chris H. Q. and Zhou, Ding and He, Xiaofeng and Zha, Hongyuan},
  booktitle = {International Conference on Machine Learning},
  year      = {2006},
  pages     = {281-288},
  doi       = {10.1145/1143844.1143880},
  url       = {https://mlanthology.org/icml/2006/ding2006icml-r/}
}