Lower Bound Theory of Nonzero Entries in Solutions of ℓ2-ℓp Minimization

By Xiaojun Chen, Fengmin Xu, Yinyu Ye. SIAM Journal on Scientific Computing, 2010

326 citations recorded by the source corpus.

Subfields: Computational Mechanics, Computer Vision and Pattern Recognition, Mathematical Physics

View Paper: https://www.semanticscholar.org/paper/232438c322108d36aadc4795f1fd0b541d0cdc72

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Mechanics

1. Jinshan Zeng
2. Wotao Yin
3. Xiaojun Chen
4. Yin Zhang
5. Ming Yan
6. Stanley J. Osher
7. Mingyi Hong
8. Yangyang Xu

In Computer Vision and Pattern Recognition

1. Xiaojun Chen
2. Wotao Yin
3. Jinshan Zeng
4. Yin Zhang
5. Stanley J. Osher
6. Junfeng Yang
7. Paul Tseng
8. Zaiwen Wen

In Mathematical Physics

1. Wotao Yin
2. Xiaojun Chen
3. Jinshan Zeng
4. Stanley J. Osher
5. Ming Yan

Citations in the corpus

• On Nonconvex Decentralized Gradient Descent (2016, background): “The proximal function ri can be taken as: 1) convex penalties such as nonsmooth 1-norm or smooth 2-norm; 2) the indicator function for a closed convex set (or a nonconvex set with an easy projection) [4], that is, ri(x) = 0 if x satisfies the constraint and∞ otherwise; 3) nonconvex penalties such as”
• Smoothing methods for nonsmooth, nonconvex minimization (2012, methodology): “is positive semi-definite, where |X| = diag(|x|) [30].”
• $L_{1/2}$ Regularization: A Thresholding Representation Theory and a Fast Solver (2012, unknown): “) A lower-bound estimation on the nonzero components of Lq solution is presented in [38].”