Pages that link to "Item:Q2840384"

The following pages link to Improved iteratively reweighted least squares for unconstrained smoothed \(\ell_q\) minimization (Q2840384):

Displaying 50 items.

• Parallel matrix factorization for low-rank tensor completion (Q256035) (← links)
• An alternating direction method with continuation for nonconvex low rank minimization (Q257130) (← links)
• Entropy function-based algorithms for solving a class of nonconvex minimization problems (Q259115) (← links)
• Two-stage convex relaxation approach to least squares loss constrained low-rank plus sparsity optimization problems (Q276859) (← links)
• A Barzilai-Borwein-like iterative half thresholding algorithm for the \(L_{1/2}\) regularized problem (Q292553) (← links)
• A smoothing SQP framework for a class of composite \(L_q\) minimization over polyhedron (Q304258) (← links)
• A rank-corrected procedure for matrix completion with fixed basis coefficients (Q312678) (← links)
• Conjugate gradient acceleration of iteratively re-weighted least squares methods (Q316180) (← links)
• Point source super-resolution via non-convex \(L_1\) based methods (Q333212) (← links)
• Exact minimum rank approximation via Schatten \(p\)-norm minimization (Q396052) (← links)
• Computing sparse representation in a highly coherent dictionary based on difference of \(L_1\) and \(L_2\) (Q493283) (← links)
• A pseudo-heuristic parameter selection rule for \(l^1\)-regularized minimization problems (Q679565) (← links)
• Two-stage convex relaxation approach to low-rank and sparsity regularized least squares loss (Q683720) (← links)
• The \(\ell_{2,q}\) regularized group sparse optimization: lower bound theory, recovery bound and algorithms (Q778013) (← links)
• A perturbation inequality for concave functions of singular values and its applications in low-rank matrix recovery (Q905912) (← links)
• Signal recovery under cumulative coherence (Q1624658) (← links)
• Global optimality condition and fixed point continuation algorithm for non-Lipschitz \(\ell_p\) regularized matrix minimization (Q1650690) (← links)
• A joint matrix minimization approach for multi-image face recognition (Q1656900) (← links)
• A patch-based low-rank tensor approximation model for multiframe image denoising (Q1675367) (← links)
• Global convergence of proximal iteratively reweighted algorithm (Q1675580) (← links)
• A globally convergent algorithm for nonconvex optimization based on block coordinate update (Q1676921) (← links)
• Virtuous smoothing for global optimization (Q1683327) (← links)
• A generalized elastic net regularization with smoothed \(\ell _{q}\) penalty for sparse vector recovery (Q1687319) (← links)
• Proximal iteratively reweighted algorithm for low-rank matrix recovery (Q1691320) (← links)
• \(\ell _p\) regularized low-rank approximation via iterative reweighted singular value minimization (Q1694395) (← links)
• An iterative support shrinking algorithm for non-Lipschitz optimization in image restoration (Q1716780) (← links)
• Enhancing matrix completion using a modified second-order total variation (Q1727032) (← links)
• A new piecewise quadratic approximation approach for \(L_0\) norm minimization problem (Q1729942) (← links)
• On monotone and primal-dual active set schemes for \(\ell^p\)-type problems, \(p \in (0,1]\) (Q1734767) (← links)
• Fast L1-L2 minimization via a proximal operator (Q1742664) (← links)
• Sparse signal recovery with prior information by iterative reweighted least squares algorithm (Q1746492) (← links)
• Minimization of transformed \(L_1\) penalty: theory, difference of convex function algorithm, and robust application in compressed sensing (Q1749455) (← links)
• Iterative reweighted methods for \(\ell _1-\ell _p\) minimization (Q1753073) (← links)
• Equivalent Lipschitz surrogates for zero-norm and rank optimization problems (Q1756795) (← links)
• Recovery of seismic wavefields by an \(l_{q}\)-norm constrained regularization method (Q1785033) (← links)
• Error bounds for rank constrained optimization problems and applications (Q1790190) (← links)
• Analysis of the ratio of \(\ell_1\) and \(\ell_2\) norms in compressed sensing (Q1979938) (← links)
• Approximate versions of proximal iteratively reweighted algorithms including an extended IP-ICMM for signal and image processing problems (Q1987437) (← links)
• A new globally convergent algorithm for non-Lipschitz \(\ell_{p}-\ell_q\) minimization (Q2000528) (← links)
• Efficient regularized regression with \(L_0\) penalty for variable selection and network construction (Q2011726) (← links)
• Numerical identification of a sparse Robin coefficient (Q2017606) (← links)
• Effective two-stage image segmentation: a new non-Lipschitz decomposition approach with convergent algorithm (Q2031758) (← links)
• Low-rank matrix recovery via regularized nuclear norm minimization (Q2036488) (← links)
• A unified primal dual active set algorithm for nonconvex sparse recovery (Q2038299) (← links)
• Low-rank factorization for rank minimization with nonconvex regularizers (Q2044472) (← links)
• A novel dictionary learning method based on total least squares approach with application in high dimensional biological data (Q2051573) (← links)
• Nonconvex and nonsmooth sparse optimization via adaptively iterative reweighted methods (Q2052389) (← links)
• An accelerated smoothing gradient method for nonconvex nonsmooth minimization in image processing (Q2059822) (← links)
• A new method based on the manifold-alternative approximating for low-rank matrix completion (Q2061479) (← links)
• Image retinex based on the nonconvex TV-type regularization (Q2063022) (← links)