Analysis and Algorithms for Some Compressed Sensing Models Based on L1/L2 Minimization
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Publication:4997175
DOI10.1137/20M1355380zbMath1470.90098arXiv2007.12821MaRDI QIDQ4997175
Liaoyuan Zeng, Ting Kei Pong, Peiran Yu
Publication date: 28 June 2021
Published in: SIAM Journal on Optimization (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2007.12821
Applications of mathematical programming (90C90) Nonconvex programming, global optimization (90C26) Fractional programming (90C32) Methods of successive quadratic programming type (90C55)
Related Items (6)
Minimization of $L_1$ Over $L_2$ for Sparse Signal Recovery with Convergence Guarantee ⋮ Study on \(L_1\) over \(L_2\) Minimization for nonnegative signal recovery ⋮ Sorted \(L_1/L_2\) minimization for sparse signal recovery ⋮ Retraction-based first-order feasible methods for difference-of-convex programs with smooth inequality and simple geometric constraints ⋮ Analysis of the ratio of \(\ell_1\) and \(\ell_2\) norms in compressed sensing ⋮ Extrapolated Proximal Subgradient Algorithms for Nonconvex and Nonsmooth Fractional Programs
Uses Software
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