3 papers
stat.ME2025
The -PCA Framework: A Unified and Efficiency-Preserving Approach with Robust Variants
Hung Hung, Zhi-Yu Jou, Su-Yun Huang +1
Principal component analysis (PCA) is a fundamental tool in multivariate statistics, yet its sensitivity to outliers and limitations in distributed environments restrict its effect…
math.ST2024
On the asymptotic properties of product-PCA under the high-dimensional setting
Hung Hung, Chi-Chun Yeh, Su-Yun Huang
Principal component analysis (PCA) is a widely used dimension reduction method, but its performance is known to be non-robust to outliers. Recently, product-PCA (PPCA) has been sho…
stat.ML2024
A Generalized Mean Approach for Distributed-PCA
Zhi-Yu Jou, Su-Yun Huang, Hung Hung +1
Principal component analysis (PCA) is a widely used technique for dimension reduction. As datasets continue to grow in size, distributed-PCA (DPCA) has become an active research ar…