Orthogonal Sparse PCA and Covariance Estimation via Procrustes Reformulation

12 Feb 2016Konstantinos BenidisYing SunPrabhu BabuDaniel P. Palomar

The problem of estimating sparse eigenvectors of a symmetric matrix attracts a lot of attention in many applications, especially those with high dimensional data set. While classical eigenvectors can be obtained as the solution of a maximization problem, existing approaches formulate this problem by adding a penalty term into the objective function that encourages a sparse solution... (read more)

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