On the equivalent of low-rank linear regressions and linear discriminant analysis based regressions

@inproceedings{Cai2013OnTE,
  title={On the equivalent of low-rank linear regressions and linear discriminant analysis based regressions},
  author={Xiao Cai and Chris H. Q. Ding and Feiping Nie and Heng Huang},
  booktitle={KDD},
  year={2013}
}
The low-rank regression model has been studied and applied to capture the underlying classes/tasks correlation patterns, such that the regression/classification results can be enhanced. In this paper, we will prove that the low-rank regression model is equivalent to doing linear regression in the linear discriminant analysis (LDA) subspace. Our new theory reveals the learning mechanism of low-rank regression, and shows that the low-rank structures exacted from classes/tasks are connected to the… CONTINUE READING
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