3 papers
stat.ME2025
Debiased distributed PCA under high dimensional spiked model
Weiming Li, Zeng Li, Siyu Wang +2
We study distributed principal component analysis (PCA) in high-dimensional settings under the spiked model. In such regimes, sample eigenvectors can deviate significantly from pop…
cs.LG2025
FoLDTree: A ULDA-Based Decision Tree Framework for Efficient Oblique Splits and Feature Selection
Siyu Wang, Kehui Yao
Traditional decision trees are limited by axis-orthogonal splits, which can perform poorly when true decision boundaries are oblique. While oblique decision tree methods address th…
stat.ME2025
A New Forward Discriminant Analysis Framework Based On Pillai's Trace and ULDA
Siyu Wang, Kehui Yao
Linear discriminant analysis (LDA), a traditional classification tool, suffers from limitations such as sensitivity to noise and computational challenges when dealing with non-inve…