Pages that link to "Item:Q734955"

The following pages link to Enhancing sparsity by reweighted \(\ell _{1}\) minimization (Q734955):

Displaying 50 items.

• Some greedy algorithms for sparse polynomial chaos expansions (Q2220572) (← links)
• Mathematical programs with complementarity constraints and a non-Lipschitz objective: optimality and approximation (Q2220667) (← links)
• Hyper-Laplacian regularized nonlocal low-rank matrix recovery for hyperspectral image compressive sensing reconstruction (Q2224828) (← links)
• Bregman reweighted alternating minimization and its application to image deblurring (Q2224931) (← links)
• Bilateral filter based total variation regularization for sparse hyperspectral image unmixing (Q2225167) (← links)
• On constrained optimization with nonconvex regularization (Q2225521) (← links)
• Relating \(\ell_p\) regularization and reweighted \(\ell_1\) regularization (Q2230788) (← links)
• On the superiority of PGMs to PDCAs in nonsmooth nonconvex sparse regression (Q2230800) (← links)
• A two-step iterative algorithm for sparse hyperspectral unmixing via total variation (Q2242712) (← links)
• A LogTVSCAD nonconvex regularization model for image deblurring in the presence of impulse noise (Q2244367) (← links)
• A reweighted nuclear norm minimization algorithm for low rank matrix recovery (Q2252420) (← links)
• An approximate sparsity model for inpainting (Q2252511) (← links)
• From simple structure to sparse components: a review (Q2259727) (← links)
• Iterative reweighted noninteger norm regularizing SVM for gene expression data classification (Q2262318) (← links)
• A numerical exploration of compressed sampling recovery (Q2267399) (← links)
• Flexible GMRES for total variation regularization (Q2273198) (← links)
• Iterative re-weighted least squares algorithm for \(l_p\)-minimization with tight frame and \(0 < p \leq 1\) (Q2273889) (← links)
• Sensor selection strategies for state estimation in energy constrained wireless sensor networks (Q2276100) (← links)
• Empirical Bayesian learning in AR graphical models (Q2280924) (← links)
• A gradient descent based algorithm for \(\ell_p\) minimization (Q2286916) (← links)
• Analysis of compressed distributed adaptive filters (Q2288711) (← links)
• Numerical analysis for conservation laws using \(l_1\) minimization (Q2291861) (← links)
• A non-convex tensor rank approximation for tensor completion (Q2293872) (← links)
• Localization of mixed near-field and far-field multi-band sources based on sparse representation (Q2294492) (← links)
• Simultaneous stabilization of polynomial nonlinear systems via density functions (Q2297408) (← links)
• A new smoothed L0 regularization approach for sparse signal recovery (Q2298142) (← links)
• Superresolution 2D DOA estimation for a rectangular array via reweighted decoupled atomic norm minimization (Q2298700) (← links)
• An active set Barzilar-Borwein algorithm for \(l_0\) regularized optimization (Q2307750) (← links)
• Accelerated iterative hard thresholding algorithm for \(l_0\) regularized regression problem (Q2307753) (← links)
• Joint image compression-encryption scheme using entropy coding and compressive sensing (Q2308152) (← links)
• Divide and conquer: an incremental sparsity promoting compressive sampling approach for polynomial chaos expansions (Q2309799) (← links)
• MRI denoising via sparse tensors with reweighted regularization (Q2310559) (← links)
• The modified second APG method for DC optimization problems (Q2311112) (← links)
• Detecting edges from non-uniform Fourier data via sparse Bayesian learning (Q2316239) (← links)
• Greedy Gaussian segmentation of multivariate time series (Q2324258) (← links)
• A consistent and numerically efficient variable selection method for sparse Poisson regression with applications to learning and signal recovery (Q2329779) (← links)
• Orthogonal matched wavelets with vanishing moments: a sparsity design approach (Q2333093) (← links)
• Block matching video compression based on sparse representation and dictionary learning (Q2333095) (← links)
• Norm penalized joint-optimization NLMS algorithms for broadband sparse adaptive channel estimation (Q2333541) (← links)
• A reweighted symmetric smoothed function approximating \(L_0\)-norm regularized sparse reconstruction method (Q2333885) (← links)
• A smoothed \(l_0\)-norm and \(l_1\)-norm regularization algorithm for computed tomography (Q2337028) (← links)
• A non-convex algorithm framework based on DC programming and DCA for matrix completion (Q2340366) (← links)
• Set membership identification of switched linear systems with known number of subsystems (Q2342531) (← links)
• Error analysis of reweighted \(l_1\) greedy algorithm for noisy reconstruction (Q2345681) (← links)
• Finding sparse solutions of systems of polynomial equations via group-sparsity optimization (Q2349523) (← links)
• Rank-one and sparse matrix decomposition for dynamic MRI (Q2353466) (← links)
• Constructing optimal sparse portfolios using regularization methods (Q2355718) (← links)
• A smoothing iterative method for quantile regression with nonconvex \(\ell_p\) penalty (Q2358473) (← links)
• Use of EM algorithm for data reduction under sparsity assumption (Q2358925) (← links)
• Majorization-minimization generalized Krylov subspace methods for \({\ell _p}\)-\({\ell _q}\) optimization applied to image restoration (Q2359752) (← links)