A fast homotopy algorithm for gridless sparse recovery
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Publication:5148425
DOI10.1088/1361-6420/abd29czbMath1460.94005OpenAlexW4385618824MaRDI QIDQ5148425
Bruno Colicchio, Jean-Baptiste Courbot
Publication date: 4 February 2021
Published in: Inverse Problems (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1088/1361-6420/abd29c
Ridge regression; shrinkage estimators (Lasso) (62J07) Convex programming (90C25) Numerical optimization and variational techniques (65K10) Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)
Related Items (2)
On the uniqueness of solutions for the basis pursuit in the continuum ⋮ TV-based spline reconstruction with Fourier measurements: uniqueness and convergence of grid-based methods
Uses Software
Cites Work
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- A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
- Exact reconstruction using Beurling minimal extrapolation
- Exact support recovery for sparse spikes deconvolution
- Spike detection from inaccurate samplings
- A Proximal-Gradient Homotopy Method for the Sparse Least-Squares Problem
- Probing the Pareto Frontier for Basis Pursuit Solutions
- Fast Solution of $\ell _{1}$-Norm Minimization Problems When the Solution May Be Sparse
- A new approach to variable selection in least squares problems
- Sparse Optimization Theory and Methods
- Recovery of Sparse Translation-Invariant Signals With Continuous Basis Pursuit
- Sparse Recovery of Streaming Signals Using <formula formulatype="inline"><tex Notation="TeX">$\ell_1$</tex></formula>-Homotopy
- Homotopy Based Algorithms for $\ell _{\scriptscriptstyle 0}$-Regularized Least-Squares
- Modular proximal optimization for multidimensional total-variation regularization
- A Limited Memory Algorithm for Bound Constrained Optimization
- Inverse problems in spaces of measures
- The sliding Frank–Wolfe algorithm and its application to super-resolution microscopy
- Compressed Sensing Off the Grid
- Towards a Mathematical Theory of Super‐resolution
- The Alternating Descent Conditional Gradient Method for Sparse Inverse Problems
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