The following pages link to Compressed sensing (Q5900527):
Displaying 50 items.
- Learning to scan: a deep reinforcement learning approach for personalized scanning in CT imaging (Q2072167) (← links)
- Two-stage geometric information guided image reconstruction (Q2072570) (← links)
- Sparsest piecewise-linear regression of one-dimensional data (Q2074905) (← links)
- Structured iterative hard thresholding with on- and off-grid applications (Q2074952) (← links)
- Localized Fourier analysis for graph signal processing (Q2074996) (← links)
- Asymptotic analysis for extreme eigenvalues of principal minors of random matrices (Q2075335) (← links)
- The all-or-nothing phenomenon in sparse linear regression (Q2078961) (← links)
- Robust sparse recovery via a novel convex model (Q2079105) (← links)
- Perturbation analysis of \(L_{1-2}\) method for robust sparse recovery (Q2082139) (← links)
- Some modified fast iterative shrinkage thresholding algorithms with a new adaptive non-monotone stepsize strategy for nonsmooth and convex minimization problems (Q2082554) (← links)
- Sparse parameter identification of stochastic dynamical systems (Q2082775) (← links)
- A forward-backward greedy approach for sparse multiscale learning (Q2083098) (← links)
- Ensemble Kalman inversion for sparse learning of dynamical systems from time-averaged data (Q2083640) (← links)
- Learning ``best'' kernels from data in Gaussian process regression. With application to aerodynamics (Q2083686) (← links)
- Existence and uniqueness of solutions to the norm minimum problem on digraphs (Q2084233) (← links)
- Commonsense explanations of sparsity, Zipf law, and Nash's bargaining solution (Q2086143) (← links)
- A Lagrange-Newton algorithm for sparse nonlinear programming (Q2089792) (← links)
- Two-step inertial Bregman alternating minimization algorithm for nonconvex and nonsmooth problems (Q2089886) (← links)
- Fast and memory-optimal dimension reduction using Kac's walk (Q2090615) (← links)
- On the grouping effect of the \(l_{1-2}\) models (Q2093808) (← links)
- A convex relaxation framework consisting of a primal-dual alternative algorithm for solving \(\ell_0\) sparsity-induced optimization problems with application to signal recovery based image restoration (Q2095175) (← links)
- A family of variable step-size sparsity-aware SSAF algorithms with individual-weighting-factors under model-driven method (Q2096138) (← links)
- A class of line search-type methods for nonsmooth convex regularized minimization (Q2098339) (← links)
- Automatic balancing parameter selection for Tikhonov-TV regularization (Q2098776) (← links)
- Sensitivity of low-rank matrix recovery (Q2100520) (← links)
- GRPDA revisited: relaxed condition and connection to Chambolle-Pock's primal-dual algorithm (Q2103452) (← links)
- A phase transition for finding needles in nonlinear haystacks with LASSO artificial neural networks (Q2103975) (← links)
- Generalization bounds for sparse random feature expansions (Q2105118) (← links)
- Unbiasing in iterative reconstruction algorithms for discrete compressed sensing (Q2106477) (← links)
- Recovery under side constraints (Q2106480) (← links)
- Angular scattering function estimation using deep neural networks (Q2106483) (← links)
- Active channel sparsification: realizing frequency-division duplexing massive MIMO with minimal overhead (Q2106487) (← links)
- Compressed sensing in the spherical near-field to far-field transformation (Q2106500) (← links)
- Coarray interpolation for joint DOD and DOA estimation in bistatic coprime MIMO radar via decoupled atomic norm minimization (Q2108454) (← links)
- Adaptive iterative hard thresholding for least absolute deviation problems with sparsity constraints (Q2108537) (← links)
- Lazy regular sensing (Q2112190) (← links)
- On nondegenerate M-stationary points for sparsity constrained nonlinear optimization (Q2114575) (← links)
- Bi-fidelity reduced polynomial chaos expansion for uncertainty quantification (Q2115584) (← links)
- Duality gap estimates for a class of greedy optimization algorithms in Banach spaces (Q2117632) (← links)
- A compressed sampling receiver based on modulated wideband converter and a parameter estimation algorithm for fractional bandlimited LFM signals (Q2118689) (← links)
- Efficient projection algorithms onto the weighted \(\ell_1\) ball (Q2124458) (← links)
- Derandomized compressed sensing with nonuniform guarantees for \(\ell_1\) recovery (Q2124653) (← links)
- Model recovery for multi-input signal-output nonlinear systems based on the compressed sensing recovery theory (Q2125313) (← links)
- Exploiting prior knowledge in compressed sensing to design robust systems for endoscopy image recovery (Q2125346) (← links)
- An efficient approach for encrypting double color images into a visually meaningful cipher image using 2D compressive sensing (Q2127056) (← links)
- On the randomised stability constant for inverse problems (Q2128524) (← links)
- Generative imaging and image processing via generative encoder (Q2128594) (← links)
- Sparse solutions to an underdetermined system of linear equations via penalized Huber loss (Q2129205) (← links)
- Sparse high-dimensional linear regression. Estimating squared error and a phase transition (Q2131259) (← links)
- Stable high-order cubature formulas for experimental data (Q2133503) (← links)
