2 papers
math.NA2025
Outlier-aware Tensor Robust Principal Component Analysis with Self-guided Data Augmentation
Yangyang Xu, Kexin Li, Li Yang +1
Tensor Robust Principal Component Analysis (TRPCA) is a fundamental technique for decomposing multi-dimensional data into a low-rank tensor and an outlier tensor, yet existing meth…
cs.LG2024
Robust PCA Based on Adaptive Weighted Least Squares and Low-Rank Matrix Factorization
Kexin Li, You-wei Wen, Xu Xiao +1
Robust Principal Component Analysis (RPCA) is a fundamental technique for decomposing data into low-rank and sparse components, which plays a critical role for applications such as…