Pages that link to "Item:Q3068374"
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The following pages link to Necessary and sufficient conditions for linear convergence of ℓ1-regularization (Q3068374):
Displaying 50 items.
- Empirical average-case relation between undersampling and sparsity in X-ray CT (Q256004) (← links)
- A unified approach to convergence rates for \(\ell^{1}\)-regularization and lacking sparsity (Q278020) (← links)
- The residual method for regularizing ill-posed problems (Q425458) (← links)
- An infeasible-point subgradient method using adaptive approximate projections (Q461434) (← links)
- On uniqueness guarantees of solution in convex regularized linear inverse problems (Q498340) (← links)
- On the solution uniqueness characterization in the L1 norm and polyhedral gauge recovery (Q511961) (← links)
- Injectivity and \(\text{weak}^\star\)-to-weak continuity suffice for convergence rates in \(\ell^{1}\)-regularization (Q682035) (← links)
- Improved bounds for restricted isometry constants (Q714287) (← links)
- Exact support recovery for sparse spikes deconvolution (Q887157) (← links)
- Optimal dual certificates for noise robustness bounds in compressive sensing (Q892815) (← links)
- Sparse signal inversion with impulsive noise by dual spectral projected gradient method (Q1992541) (← links)
- Maximal spaces for approximation rates in \(\ell^1\)-regularization (Q2055984) (← links)
- Infinite-dimensional inverse problems with finite measurements (Q2069717) (← links)
- Smoothing Newton method for \(\ell^0\)-\(\ell^2\) regularized linear inverse problem (Q2072164) (← links)
- Regularization of inverse problems by filtered diagonal frame decomposition (Q2105104) (← links)
- Adaptive multi-penalty regularization based on a generalized Lasso path (Q2175012) (← links)
- Choice of the parameters in a primal-dual algorithm for Bregman iterated variational regularization (Q2220748) (← links)
- Oscillation of metropolis-Hastings and simulated annealing algorithms around LASSO estimator (Q2229034) (← links)
- An evaluation of the sparsity degree for sparse recovery with deterministic measurement matrices (Q2251220) (← links)
- Necessary and sufficient conditions of solution uniqueness in 1-norm minimization (Q2260650) (← links)
- Convergence rates for \(\ell^1\)-regularization without the help of a variational inequality (Q2363891) (← links)
- One condition for solution uniqueness and robustness of both \(\ell_1\)-synthesis and \(\ell_1\)-analysis minimizations (Q2374380) (← links)
- Consistency of \(\ell_1\) recovery from noisy deterministic measurements (Q2450946) (← links)
- On \(\ell^1\)-regularization in light of Nashed's ill-posedness concept (Q2516860) (← links)
- Infinite dimensional compressed sensing from anisotropic measurements and applications to inverse problems in PDE (Q2659717) (← links)
- Quadratic growth conditions and uniqueness of optimal solution to Lasso (Q2671439) (← links)
- Far field splitting by iteratively reweighted \(\ell^1\) minimization (Q2799041) (← links)
- Low Complexity Regularization of Linear Inverse Problems (Q2799919) (← links)
- Uncertainty Principles for Inverse Source Problems, Far Field Splitting, and Data Completion (Q2957323) (← links)
- Geometric properties of solutions to the total variation denoising problem (Q2971437) (← links)
- Testable uniqueness conditions for empirical assessment of undersampling levels in total variation-regularized X-ray CT (Q3456555) (← links)
- Regularized sparse representation for image deconvolution (Q3465079) (← links)
- Sensitivity Analysis for Mirror-Stratifiable Convex Functions (Q4554065) (← links)
- On ℓ 1 -Regularization Under Continuity of the Forward Operator in Weaker Topologies (Q4554173) (← links)
- Inverse problems with nonnegative and sparse solutions: algorithms and application to the phase retrieval problem (Q4569355) (← links)
- Efficient regularization with wavelet sparsity constraints in photoacoustic tomography (Q4607820) (← links)
- Sparse Regularization of Inverse Problems by Operator-Adapted Frame Thresholding (Q4964112) (← links)
- Convergence rates in<i>ℓ</i><sup>1</sup>-regularization when the basis is not smooth enough (Q4982025) (← links)
- Variational regularization theory based on image space approximation rates (Q4993904) (← links)
- Convergence rates for the joint solution of inverse problems with compressed sensing data (Q5058467) (← links)
- Shearlet-based regularization in statistical inverse learning with an application to x-ray tomography (Q5071173) (← links)
- NETT: solving inverse problems with deep neural networks (Q5113628) (← links)
- Deep synthesis network for regularizing inverse problems (Q5150821) (← links)
- Weak Stability of <i>ℓ</i><sub>1</sub>-Minimization Methods in Sparse Data Reconstruction (Q5219713) (← links)
- Modern regularization methods for inverse problems (Q5230515) (← links)
- Solving Basis Pursuit (Q5270711) (← links)
- Compressive time-of-flight 3D imaging using block-structured sensing matrices (Q5382462) (← links)
- Optimal convergence rates for sparsity promoting wavelet-regularization in Besov spaces (Q5383317) (← links)
- An introduction to continuous optimization for imaging (Q5740077) (← links)
- Multiscale Factorization of the Wave Equation with Application to Compressed Sensing Photoacoustic Tomography (Q5860294) (← links)
