2 papers
stat.ML2025
Transformed Regularizations for Robust Principal Component Analysis: Toward a Fine-Grained Understanding
Kun Zhao, Haoke Zhang, Jiayi Wang +1
Robust Principal Component Analysis (RPCA) aims to recover a low-rank structure from noisy, partially observed data that is also corrupted by sparse, potentially large-magnitude ou…
math.ST2025
Noisy Low-Rank Matrix Completion via Transformed Regularization and its Theoretical Properties
Kun Zhao, Jiayi Wang, Yifei Lou
This paper focuses on recovering an underlying matrix from its noisy partial entries, a problem commonly known as matrix completion. We delve into the investigation of a non-convex…