De-biased sparse PCA: Inference and testing for eigenstructure of large covariance matrices

Jana Janková, Sara van de Geer

Sparse principal component analysis (sPCA) has become one of the most widely used techniques for dimensionality reduction in high-dimensional datasets. The main challenge underlyin…