Pages that link to "Item:Q5650816"
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The following pages link to Perturbation bounds in connection with singular value decomposition (Q5650816):
Displaying 50 items.
- Angle-based joint and individual variation explained (Q130628) (← links)
- On two continuum armed bandit problems in high dimensions (Q260274) (← links)
- On perturbation bounds for orthogonal projections (Q329317) (← links)
- Sparse principal component analysis and iterative thresholding (Q355104) (← links)
- Reconstruction of a low-rank matrix in the presence of Gaussian noise (Q391623) (← links)
- Learning functions of few arbitrary linear parameters in high dimensions (Q434415) (← links)
- Residual bounds for some or all singular values (Q466506) (← links)
- Detection, reconstruction, and characterization algorithms from noisy data in multistatic wave imaging (Q479102) (← links)
- Finding a low-rank basis in a matrix subspace (Q517309) (← links)
- Learning non-parametric basis independent models from point queries via low-rank methods (Q741260) (← links)
- A Schatten-\(q\) low-rank matrix perturbation analysis via perturbation projection error bound (Q821008) (← links)
- The optimal perturbation bounds of the Moore-Penrose inverse under the Frobenius norm (Q846324) (← links)
- Perturbation of the SVD in the presence of small singular values (Q854854) (← links)
- Minimax estimation in sparse canonical correlation analysis (Q888508) (← links)
- On the accuracy of total least squares and least squares techniques in the presence of errors on all data (Q912059) (← links)
- Multiplicative perturbation bounds for spectral and singular value decompositions (Q929924) (← links)
- Consistent estimation in an implicit quadratic measurement error model (Q956994) (← links)
- On perturbations of some constrained subspaces (Q1008676) (← links)
- A perturbation analysis of the intrinsic conditioning of an approximate null vector computed with a SVD (Q1056197) (← links)
- An SVD analysis of linear algebraic equations derived from first kind integral equations (Q1065526) (← links)
- The truncated SVD as a method for regularization (Q1096333) (← links)
- Algebraic connections between the least squares and total least squares problems (Q1114307) (← links)
- Computational methods of linear algebra (Q1148099) (← links)
- Perturbation analysis of the canonical subspaces (Q1307563) (← links)
- Backward perturbation analysis of certain characteristic subspaces (Q1326455) (← links)
- History and generality of the CS decomposition (Q1336415) (← links)
- Perturbation bounds for the least squares problem (Q1364065) (← links)
- CGLS-GCV: A hybrid algorithm for low-rank-deficient problems. (Q1412332) (← links)
- Relative perturbation theory. IV: \(\sin 2\theta\) theorems (Q1567544) (← links)
- A new relative perturbation theorem for singular subspaces (Q1579512) (← links)
- Random perturbation of low rank matrices: improving classical bounds (Q1688904) (← links)
- Accuracy of singular vectors obtained by projection-based SVD methods (Q1689319) (← links)
- Rate-optimal perturbation bounds for singular subspaces with applications to high-dimensional statistics (Q1747733) (← links)
- Perturbation theory for the Eckart-Young-Mirsky theorem and the constrained total least squares problem (Q1808940) (← links)
- Fitting conics of specific types to data (Q1826713) (← links)
- Consistent fundamental matrix estimation in a quadratic measurement error model arising in motion analysis (Q1874116) (← links)
- Weyl-type relative perturbation bounds for eigensystems of Hermitian matrices (Q1976905) (← links)
- A locally optimal rank revealing product decomposition (Q2029861) (← links)
- Robust high-dimensional factor models with applications to statistical machine learning (Q2038305) (← links)
- Perturbation expansions and error bounds for the truncated singular value decomposition (Q2041768) (← links)
- Convex combination of data matrices: PCA perturbation bounds for multi-objective optimal design of mechanical metafilters (Q2065508) (← links)
- An \({\ell_p}\) theory of PCA and spectral clustering (Q2091846) (← links)
- Stable recovery of entangled weights: towards robust identification of deep neural networks from minimal samples (Q2105108) (← links)
- Robust and resource-efficient identification of two hidden layer neural networks (Q2117339) (← links)
- Heteroskedastic PCA: algorithm, optimality, and applications (Q2119219) (← links)
- Lower bounds on Anderson-localised eigenfunctions on a strip (Q2129293) (← links)
- Generalization error of random feature and kernel methods: hypercontractivity and kernel matrix concentration (Q2134105) (← links)
- Non-asymptotic properties of spectral decomposition of large Gram-type matrices and applications (Q2137016) (← links)
- Smoothed analysis for tensor methods in unsupervised learning (Q2144543) (← links)
- Optimization landscape of Tucker decomposition (Q2144548) (← links)
