Finding sparse solutions of systems of polynomial equations via group-sparsity optimization
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Publication:2349523
DOI10.1007/s10898-014-0225-8zbMath1347.90078arXiv1311.5871OpenAlexW2092754161MaRDI QIDQ2349523
Publication date: 22 June 2015
Published in: Journal of Global Optimization (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1311.5871
Related Items (4)
An iterative method for finding the least solution to the tensor complementarity problem ⋮ An Inexact Projected Gradient Method for Sparsity-Constrained Quadratic Measurements Regression ⋮ Iteratively Reweighted Group Lasso Based on Log-Composite Regularization ⋮ The sparsest solutions to \(Z\)-tensor complementarity problems
Uses Software
Cites Work
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- A mathematical introduction to compressive sensing
- TAGE iterative algorithm and nonpolynomial spline basis for the solution of nonlinear singular second order ordinary differential equations
- Enhancing sparsity by reweighted \(\ell _{1}\) minimization
- A predictor-corrector algorithm for the coupling of stiff ODEs to a particle population balance
- Saving phase: injectivity and stability for phase retrieval
- On signal reconstruction without phase
- PhaseLift: Exact and Stable Signal Recovery from Magnitude Measurements via Convex Programming
- Sparsity Constrained Nonlinear Optimization: Optimality Conditions and Algorithms
- Selective <inline-formula> <tex-math notation="TeX">$\ell_{1}$</tex-math></inline-formula> Minimization for Sparse Recovery
- Compressed Sensing With Nonlinear Observations and Related Nonlinear Optimization Problems
- Graph Implementations for Nonsmooth Convex Programs
- Stable recovery of sparse overcomplete representations in the presence of noise
- From Sparse Solutions of Systems of Equations to Sparse Modeling of Signals and Images
- Uncertainty principles and ideal atomic decomposition
- Super Resolution Phase Retrieval for Sparse Signals
- Quasi-linear Compressed Sensing
- Phase Retrieval via Matrix Completion
- Compressed sensing
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