Pages that link to "Item:Q5280996"

The following pages link to Tight Oracle Inequalities for Low-Rank Matrix Recovery From a Minimal Number of Noisy Random Measurements (Q5280996):

Displaying 50 items.

• An inexact proximal DC algorithm with sieving strategy for rank constrained least squares semidefinite programming (Q2148144) (← links)
• On the robustness of noise-blind low-rank recovery from rank-one measurements (Q2168911) (← links)
• Guarantees of Riemannian optimization for low rank matrix completion (Q2176515) (← links)
• High-dimensional VAR with low-rank transition (Q2195856) (← links)
• A multi-stage convex relaxation approach to noisy structured low-rank matrix recovery (Q2220914) (← links)
• Theoretical investigation of generalization bounds for adversarial learning of deep neural networks (Q2241474) (← links)
• Sharp RIP bound for sparse signal and low-rank matrix recovery (Q2252129) (← links)
• Convergence of projected Landweber iteration for matrix rank minimization (Q2252213) (← links)
• Sparse recovery with coherent tight frames via analysis Dantzig selector and analysis LASSO (Q2252508) (← links)
• RIP-based performance guarantee for low-tubal-rank tensor recovery (Q2306402) (← links)
• Approximation of generalized ridge functions in high dimensions (Q2315030) (← links)
• Truncated sparse approximation property and truncated \(q\)-norm minimization (Q2322801) (← links)
• Non-intrusive tensor reconstruction for high-dimensional random PDEs (Q2324350) (← links)
• Optimal RIP bounds for sparse signals recovery via \(\ell_p\) minimization (Q2330928) (← links)
• ROP: matrix recovery via rank-one projections (Q2338922) (← links)
• Stable recovery of low rank matrices from nuclear norm minimization (Q2343583) (← links)
• Stable recovery of analysis based approaches (Q2347901) (← links)
• Convergence and stability of iteratively reweighted least squares for low-rank matrix recovery (Q2360780) (← links)
• Low rank tensor recovery via iterative hard thresholding (Q2400255) (← links)
• Iterative hard thresholding for low-rank recovery from rank-one projections (Q2419026) (← links)
• RIPless compressed sensing from anisotropic measurements (Q2437334) (← links)
• On a unified view of nullspace-type conditions for recoveries associated with general sparsity structures (Q2437335) (← links)
• Asymptotic equivalence of quantum state tomography and noisy matrix completion (Q2438759) (← links)
• Convergence analysis of projected gradient descent for Schatten-\(p\) nonconvex matrix recovery (Q2515314) (← links)
• Stable recovery of low-rank matrix via nonconvex Schatten \(p\)-minimization (Q2629808) (← links)
• On the Schatten \(p\)-quasi-norm minimization for low-rank matrix recovery (Q2659733) (← links)
• Robust recovery of low-rank matrices with non-orthogonal sparse decomposition from incomplete measurements (Q2662546) (← links)
• Terracini convexity (Q2687050) (← links)
• Regularized sample average approximation for high-dimensional stochastic optimization under low-rankness (Q2687436) (← links)
• Adaptive iterative hard thresholding for low-rank matrix recovery and rank-one measurements (Q2693686) (← links)
• Sharp variable selection of a sparse submatrix in a high-dimensional noisy matrix (Q2786472) (← links)
• Low Complexity Regularization of Linear Inverse Problems (Q2799919) (← links)
• Recovery of low rank symmetric matrices via Schatten \(p\) norm minimization (Q2800802) (← links)
• Guarantees of Riemannian optimization for low rank matrix recovery (Q2818273) (← links)
• Low Rank Estimation of Similarities on Graphs (Q2840345) (← links)
• Exact low-rank matrix recovery via nonconvex Schatten \(p\)-minimization (Q2846490) (← links)
• On Cross-Validation for Sparse Reduced Rank Regression (Q3120104) (← links)
• Truncated $l_{1-2}$ Models for Sparse Recovery and Rank Minimization (Q3130749) (← links)
• Median-Truncated Gradient Descent: A Robust and Scalable Nonconvex Approach for Signal Estimation (Q3296183) (← links)
• Linear independence oracles and applications to rectangular and low rank linear systems (Q3452420) (← links)
• Sparse Model Uncertainties in Compressed Sensing with Application to Convolutions and Sporadic Communication (Q3460837) (← links)
• Tensor Completion in Hierarchical Tensor Representations (Q3460842) (← links)
• (Q4558196) (← links)
• (Q4558476) (← links)
• Time for dithering: fast and quantized random embeddings via the restricted isometry property (Q4603715) (← links)
• High-dimensional estimation with geometric constraints: Table 1. (Q4603716) (← links)
• Near-optimal estimation of simultaneously sparse and low-rank matrices from nested linear measurements (Q4603729) (← links)
• Stable low-rank matrix recovery via null space properties (Q4606522) (← links)
• On the Quadratic Convergence of the Cubic Regularization Method under a Local Error Bound Condition (Q4634142) (← links)
• Regularization and the small-ball method II: complexity dependent error rates (Q4637079) (← links)