Pages that link to "Item:Q4651902"

The following pages link to An iterative thresholding algorithm for linear inverse problems with a sparsity constraint (Q4651902):

Displaying 50 items.

• A fast and efficient smoothing approach to Lasso regression and an application in statistical genetics: polygenic risk scores for chronic obstructive pulmonary disease (COPD) (Q2058755) (← links)
• A sparse optimization problem with hybrid \(L_2\)-\(L_p\) regularization for application of magnetic resonance brain images (Q2060052) (← links)
• A linearly convergent algorithm without prior knowledge of operator norms for solving \(\ell_1 - \ell_2\) minimization (Q2060804) (← links)
• Image restoration based on fractional-order model with decomposition: texture and cartoon (Q2064956) (← links)
• A regularized alternating direction method of multipliers for a class of nonconvex problems (Q2067949) (← links)
• A mathematical approach towards THz tomography for non-destructive imaging (Q2072160) (← links)
• Smoothing Newton method for \(\ell^0\)-\(\ell^2\) regularized linear inverse problem (Q2072164) (← links)
• An accelerated viscosity forward-backward splitting algorithm with the linesearch process for convex minimization problems (Q2072801) (← links)
• Super-resolution for doubly-dispersive channel estimation (Q2073137) (← links)
• Structured iterative hard thresholding with on- and off-grid applications (Q2074952) (← links)
• Low-rank matrix denoising for count data using unbiased Kullback-Leibler risk estimation (Q2076123) (← links)
• Generalized Nesterov's accelerated proximal gradient algorithms with convergence rate of order \(o(1/k^2)\) (Q2082553) (← links)
• \(l^1\)-weighted regularization for the problem of recovering sparse initial conditions in parabolic equations from final measurements (Q2085702) (← links)
• An inertial proximal partially symmetric ADMM-based algorithm for linearly constrained multi-block nonconvex optimization problems with applications (Q2087522) (← links)
• Information criteria bias correction for group selection (Q2093122) (← links)
• Simultaneous identification of initial value and source strength in a transmission problem for a parabolic equation (Q2095542) (← links)
• Penalized wavelet estimation and robust denoising for irregular spaced data (Q2095705) (← links)
• LASSO for streaming data with adaptative filtering (Q2104007) (← links)
• Regularization of inverse problems by filtered diagonal frame decomposition (Q2105104) (← links)
• Compressive sensing and neural networks from a statistical learning perspective (Q2106482) (← links)
• Deep learning architectures for nonlinear operator functions and nonlinear inverse problems (Q2113263) (← links)
• An inertial semi-forward-reflected-backward splitting and its application (Q2115203) (← links)
• Feasibility of DEIM for retrieving the initial field via dimensionality reduction (Q2120024) (← links)
• An inverse problem study related to a fractional diffusion equation (Q2122177) (← links)
• Oversmoothing regularization with \(\ell^1\)-penalty term (Q2127828) (← links)
• Deep learning for inverse problems. Abstracts from the workshop held March 7--13, 2021 (hybrid meeting) (Q2131206) (← links)
• An efficient gradient-free projection algorithm for constrained nonlinear equations and image restoration (Q2131452) (← links)
• Modified Tseng's splitting algorithms for the sum of two monotone operators in Banach spaces (Q2133233) (← links)
• An accelerated forward-backward algorithm with a new linesearch for convex minimization problems and its applications (Q2133344) (← links)
• Accelerated proximal gradient method for bi-modulus static elasticity (Q2138312) (← links)
• An accelerated coordinate gradient descent algorithm for non-separable composite optimization (Q2139254) (← links)
• Deep solution operators for variational inequalities via proximal neural networks (Q2146915) (← links)
• Sparse optimization on measures with over-parameterized gradient descent (Q2149558) (← links)
• A generalized proximal linearized algorithm for DC functions with application to the optimal size of the firm problem (Q2158622) (← links)
• Proximal algorithm for minimization problems in \(l_0\)-regularization for nonlinear inverse problems (Q2163465) (← links)
• Sparse minimax portfolio and Sharpe ratio models (Q2165774) (← links)
• A parallel Tseng's splitting method for solving common variational inclusion applied to signal recovery problems (Q2167271) (← links)
• Iterative method with inertial terms for nonexpansive mappings: applications to compressed sensing (Q2173332) (← links)
• Numerical reconstruction of the spatial component in the source term of a time-fractional diffusion equation (Q2178836) (← links)
• Image restoration from noisy incomplete frequency data by alternative iteration scheme (Q2188154) (← links)
• Sparse signal reconstruction via the approximations of \(\ell_0\) quasinorm (Q2190319) (← links)
• Identification of piecewise constant Robin coefficient for the Stokes problem using the Levenberg-Marquardt method (Q2190881) (← links)
• A smoothing method for sparse optimization over convex sets (Q2191281) (← links)
• Alternating forward-backward splitting for linearly constrained optimization problems (Q2191282) (← links)
• Adaptive spatial-spectral dictionary learning for hyperspectral image restoration (Q2193537) (← links)
• Three-operator splitting algorithm for a class of variational inclusion problems (Q2196426) (← links)
• Testing and non-linear preconditioning of the proximal point method (Q2198162) (← links)
• A Barzilai-Borwein gradient projection method for sparse signal and blurred image restoration (Q2198630) (← links)
• Collaborative block compressed sensing reconstruction with dual-domain sparse representation (Q2200689) (← links)
• Iterative \(p\)-shrinkage thresholding algorithm for low Tucker rank tensor recovery (Q2212078) (← links)