# American Institute of Mathematical Sciences

February  2013, 7(1): 305-306. doi: 10.3934/ipi.2013.7.305

## A short note on strongly convex programming for exact matrix completion and robust principal component analysis

 1 School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, 611731, China, China 2 Department of Electrical Engineering, ESAT-SCD / IBBT - KU, Leuven Future Health Department, KU Leuven, Kasteelpark Arenberg 10, box 2446, 3001 Heverlee, Belgium

Received  July 2012 Revised  November 2012 Published  February 2013

In paper "Strongly Convex Programming for Exact Matrix Completion and Robust Principal Component Analysis", an explicit lower bound of $\tau$ is strongly based on Theorem 3.4. However, a coefficient is missing in the proof of Theorem 3.4, which leads to improper result. In this paper, we correct this error and provide the right bound of $\tau$.
Citation: Qingshan You, Qun Wan, Yipeng Liu. A short note on strongly convex programming for exact matrix completion and robust principal component analysis. Inverse Problems & Imaging, 2013, 7 (1) : 305-306. doi: 10.3934/ipi.2013.7.305
##### References:
 [1] Hui Zhang, Jian-Feng Cai, Lizhi Cheng and Jubo Zhu, Strongly convex programming for exact matrix completion and robust principal component analysis, Inverse Problems and Imaging, 6 (2012), 357-372. doi: 10.3934/ipi.2012.6.357.  Google Scholar

show all references

##### References:
 [1] Hui Zhang, Jian-Feng Cai, Lizhi Cheng and Jubo Zhu, Strongly convex programming for exact matrix completion and robust principal component analysis, Inverse Problems and Imaging, 6 (2012), 357-372. doi: 10.3934/ipi.2012.6.357.  Google Scholar

2020 Impact Factor: 1.639

## Metrics

• HTML views (0)
• Cited by (4)

• on AIMS