The following pages link to Compressed sensing (Q5900527):
Displaying 50 items.
- On the convergence of the iterates of proximal gradient algorithm with extrapolation for convex nonsmooth minimization problems (Q2010091) (← links)
- Lagrangian duality and saddle points for sparse linear programming (Q2010427) (← links)
- Learning latent variable Gaussian graphical model for biomolecular network with low sample complexity (Q2011725) (← links)
- Sparse parallel MRI based on accelerated operator splitting schemes (Q2013007) (← links)
- An efficient algorithm based on sparse optimization for the aircraft departure scheduling problem (Q2013610) (← links)
- Properties and iterative methods for the \(Q\)-lasso (Q2015266) (← links)
- A sharp RIP condition for orthogonal matching pursuit (Q2015581) (← links)
- Compressed data separation via dual frames based split-analysis with Weibull matrices (Q2016924) (← links)
- An augmented Lagrangian algorithm for total bounded variation regularization based image deblurring (Q2017238) (← links)
- Complexity and applications of the homotopy principle for uniformly constrained sparse minimization (Q2019907) (← links)
- An algorithm for the minimization of nonsmooth nonconvex functions using inexact evaluations and its worst-case complexity (Q2020598) (← links)
- Sequential sparse Bayesian learning with applications to system identification for damage assessment and recursive reconstruction of image sequences (Q2020862) (← links)
- Novel sparseness-inducing dual Kalman filter and its application to tracking time-varying spatially-sparse structural stiffness changes and inputs (Q2021040) (← links)
- Linear convergence of inexact descent method and inexact proximal gradient algorithms for lower-order regularization problems (Q2022292) (← links)
- On recovery guarantees for one-bit compressed sensing on manifolds (Q2022611) (← links)
- Quaternary splitting algorithm in group testing (Q2025097) (← links)
- A golden ratio primal-dual algorithm for structured convex optimization (Q2025858) (← links)
- Stable phaseless sampling and reconstruction of real-valued signals with finite rate of innovation (Q2026544) (← links)
- Tractable ADMM schemes for computing KKT points and local minimizers for \(\ell_0\)-minimization problems (Q2026765) (← links)
- Sparse harmonic transforms: a new class of sublinear-time algorithms for learning functions of many variables (Q2031058) (← links)
- Convergent inexact penalty decomposition methods for cardinality-constrained problems (Q2031962) (← links)
- Low-rank matrix completion in a general non-orthogonal basis (Q2032243) (← links)
- A study on distributed optimization over large-scale networked systems (Q2036031) (← links)
- Sparse recovery in bounded Riesz systems with applications to numerical methods for PDEs (Q2036421) (← links)
- Nonlinear spectral decompositions by gradient flows of one-homogeneous functionals (Q2037455) (← links)
- Application of ESN prediction model based on compressed sensing in stock market (Q2038120) (← links)
- A unified primal dual active set algorithm for nonconvex sparse recovery (Q2038299) (← links)
- MRI simulation-based evaluation of an efficient under-sampling approach (Q2038799) (← links)
- An optimization problem arising in CR geometry (Q2039742) (← links)
- On the \(\ell^\infty\)-norms of the singular vectors of arbitrary powers of a difference matrix with applications to sigma-delta quantization (Q2040542) (← links)
- Separable collusion-secure multimedia codes (Q2044131) (← links)
- Donoho-Logan large sieve principles for modulation and polyanalytic Fock spaces (Q2046116) (← links)
- Level-set subdifferential error bounds and linear convergence of Bregman proximal gradient method (Q2046546) (← links)
- A rolling bearing fault detection method based on compressed sensing and a neural network (Q2047853) (← links)
- Tensor theta norms and low rank recovery (Q2048814) (← links)
- On Bayesian posterior mean estimators in imaging sciences and Hamilton-Jacobi partial differential equations (Q2051535) (← links)
- Dual-density-based reweighted \(\ell_1\)-algorithms for a class of \(\ell_0\)-minimization problems (Q2052391) (← links)
- Nonuniqueness of solutions of a class of \(\ell_0\)-minimization problems (Q2059197) (← links)
- Memoryless scalar quantization for random frames (Q2059810) (← links)
- A sparse optimization problem with hybrid \(L_2\)-\(L_p\) regularization for application of magnetic resonance brain images (Q2060052) (← links)
- An improved linear convergence of FISTA for the LASSO problem with application to CT image reconstruction (Q2060059) (← links)
- Adaboost-based ensemble of polynomial chaos expansion with adaptive sampling (Q2060149) (← links)
- Sparse approximate solutions to max-plus equations (Q2061850) (← links)
- RWRM: residual Wasserstein regularization model for image restoration (Q2063015) (← links)
- Inpainting via sparse recovery with directional constraints (Q2063335) (← links)
- Energy levels estimation on a quantum computer by evolution of a physical quantity (Q2064205) (← links)
- Image reconstruction based on improved block compressed sensing (Q2064972) (← links)
- Efficiency of orthogonal super greedy algorithm under the restricted isometry property (Q2067856) (← links)
- An inexact proximal gradient algorithm with extrapolation for a class of nonconvex nonsmooth optimization problems (Q2067857) (← links)
- Smoothing Newton method for \(\ell^0\)-\(\ell^2\) regularized linear inverse problem (Q2072164) (← links)
