Sparse PCA with Oracle Property

  title={Sparse PCA with Oracle Property},
  author={Quanquan Gu and Zhaoran Wang and Han Liu},
  journal={Advances in neural information processing systems},
In this paper, we study the estimation of the k-dimensional sparse principal subspace of covariance matrix Σ in the high-dimensional setting. We aim to recover the oracle principal subspace solution, i.e., the principal subspace estimator obtained assuming the true support is known a priori. To this end, we propose a family of estimators based on the semidefinite relaxation of sparse PCA with novel regularizations. In particular, under a weak assumption on the magnitude of the population… CONTINUE READING
9 Citations
29 References
Similar Papers


Publications referenced by this paper.
Showing 1-10 of 29 references

Sparsistency and agnostic inference in sparse PCA

  • J. Lei, V. Q. Vu
  • arXiv preprint arXiv:1401.6978,
  • 2014
Highly Influential
7 Excerpts

Nearly unbiased variable selection under minimax concave penalty

  • C.-H. Zhang
  • Ann. Statist.,
  • 2010
Highly Influential
7 Excerpts

Similar Papers

Loading similar papers…