2 papers
stat.ML2026
A Randomized Algorithm for Sparse PCA based on the Basic SDP Relaxation
Alberto Del Pia, Dekun Zhou
Sparse Principal Component Analysis (SPCA) is a fundamental technique for dimensionality reduction, and is NP-hard. In this paper, we introduce a randomized approximation algorithm…
cs.LG2025
Efficient Sparse PCA via Block-Diagonalization
Alberto Del Pia, Dekun Zhou, Yinglun Zhu
Sparse Principal Component Analysis (Sparse PCA) is a pivotal tool in data analysis and dimensionality reduction. However, Sparse PCA is a challenging problem in both theory and pr…