Hidden Convexity of Fair
Hidden Convexity of Fair PCA and Fast Solver via Eigenvalue Optimization
Hidden Convexity of Fair PCA and Fast Solver via Eigenvalue Optimization
arXiv:2503.00299v1 Announce Type: new
Abstract: Principal Component Analysis (PCA) is a foundational technique in machine learning for dimensionality reduction of high-dimensional datasets. However, PCA could lead to biased outcomes that disadvantage certain subgroups of the underlying datasets. To…