Pages that link to "Item:Q4834376"

The following pages link to Sparse Approximate Solutions to Linear Systems (Q4834376):

Displaying 50 items.

• Proof methods for robust low-rank matrix recovery (Q2106469) (← links)
• Sparse recovery of sound fields using measurements from moving microphones (Q2106497) (← links)
• Adaptive iterative hard thresholding for least absolute deviation problems with sparsity constraints (Q2108537) (← links)
• Ideal formulations for constrained convex optimization problems with indicator variables (Q2118117) (← links)
• Sparse representation of vectors in lattices and semigroups (Q2118144) (← links)
• Deterministic convergence analysis via smoothing group Lasso regularization and adaptive momentum for Sigma-Pi-Sigma neural network (Q2123539) (← links)
• Efficient projection algorithms onto the weighted \(\ell_1\) ball (Q2124458) (← links)
• Sparse data-driven quadrature rules via \(\ell^p\)-quasi-norm minimization (Q2134455) (← links)
• GSDAR: a fast Newton algorithm for \(\ell_0\) regularized generalized linear models with statistical guarantee (Q2135875) (← links)
• A modified orthogonal matching pursuit for construction of sparse probabilistic Boolean networks (Q2139749) (← links)
• Clustering, multicollinearity, and singular vectors (Q2143037) (← links)
• Sparse signal recovery via generalized Gaussian function (Q2154451) (← links)
• The use of grossone in elastic net regularization and sparse support vector machines (Q2156901) (← links)
• The backbone method for ultra-high dimensional sparse machine learning (Q2163249) (← links)
• Polarization in cooperative networks through optimal placement of informed agents (Q2164272) (← links)
• A solution approach for cardinality minimization problem based on fractional programming (Q2168753) (← links)
• CLOT norm minimization for continuous hands-off control (Q2173898) (← links)
• Smoothing inertial projection neural network for minimization \(L_{p-q}\) in sparse signal reconstruction (Q2179318) (← links)
• Parametrized quasi-soft thresholding operator for compressed sensing and matrix completion (Q2185044) (← links)
• Transformed \(\ell_1\) regularization for learning sparse deep neural networks (Q2185659) (← links)
• An improved total variation regularized RPCA for moving object detection with dynamic background (Q2190301) (← links)
• Sparse signal reconstruction via the approximations of \(\ell_0\) quasinorm (Q2190319) (← links)
• A smoothing method for sparse optimization over convex sets (Q2191281) (← links)
• A filtered bucket-clustering method for projection onto the simplex and the \(\ell_1\) ball (Q2191778) (← links)
• Analysis non-sparse recovery for relaxed ALASSO (Q2191835) (← links)
• Dynamic behavior analysis via structured rank minimization (Q2193906) (← links)
• Deterministic construction of compressed sensing matrices from constant dimension codes (Q2197399) (← links)
• Adaptive decomposition-based evolutionary approach for multiobjective sparse reconstruction (Q2198239) (← links)
• Effective zero-norm minimization algorithms for noisy compressed sensing (Q2198627) (← links)
• Compressive isogeometric analysis (Q2214468) (← links)
• Nonconvex optimization for robust tensor completion from grossly sparse observations (Q2219800) (← links)
• Some greedy algorithms for sparse polynomial chaos expansions (Q2220572) (← links)
• Sparse regression: scalable algorithms and empirical performance (Q2225311) (← links)
• Best subset, forward stepwise or Lasso? Analysis and recommendations based on extensive comparisons (Q2225312) (← links)
• The complexity results of the sparse optimization problems and reverse convex optimization problems (Q2228394) (← links)
• Matrix recipes for hard thresholding methods (Q2251217) (← links)
• The nonnegative zero-norm minimization under generalized \(Z\)-matrix measurement (Q2251573) (← links)
• Convergence of projected Landweber iteration for matrix rank minimization (Q2252213) (← links)
• Fast thresholding algorithms with feedbacks for sparse signal recovery (Q2252504) (← links)
• Sparse recovery with coherent tight frames via analysis Dantzig selector and analysis LASSO (Q2252508) (← links)
• Solving \(\ell_0\)-penalized problems with simple constraints via the Frank-Wolfe reduced dimension method (Q2257078) (← links)
• On rank awareness, thresholding, and MUSIC for joint sparse recovery (Q2278470) (← links)
• Recovering low-rank and sparse matrix based on the truncated nuclear norm (Q2281698) (← links)
• An efficient optimization approach for best subset selection in linear regression, with application to model selection and fitting in autoregressive time-series (Q2282827) (← links)
• Sparsity in max-plus algebra and systems (Q2286330) (← links)
• A new sparse recovery method for the inverse acoustic scattering problem (Q2300540) (← links)
• An active set Barzilar-Borwein algorithm for \(l_0\) regularized optimization (Q2307750) (← links)
• The sparsest solution of the union of finite polytopes via its nonconvex relaxation (Q2311128) (← links)
• Nonsmooth sparsity constrained optimization problems: optimality conditions (Q2311196) (← links)
• Deterministic constructions of compressed sensing matrices based on codes (Q2311429) (← links)