Pages that link to "Item:Q5896779"

The following pages link to Generalized low rank approximations of matrices (Q5896779):

Displaying 50 items.

• Denoising color images by reduced quaternion matrix singular value decomposition (Q336045) (← links)
• On the low-rank approximation arising in the generalized Karhunen-Loeve transform (Q370011) (← links)
• Matrix-variate and higher-order probabilistic projections (Q408620) (← links)
• Incremental tensor subspace learning and its applications to foreground segmentation and tracking (Q408862) (← links)
• A survey on rank and inertia optimization problems of the matrix-valued function \(A+BXB^\ast\) (Q494274) (← links)
• Decomposition into low-rank plus additive matrices for background/foreground separation: a review for a comparative evaluation with a large-scale dataset (Q518124) (← links)
• Double-fold localized multiple matrixized learning machine (Q527144) (← links)
• Two-dimensional random projection (Q537260) (← links)
• Orthogonal tensor neighborhood preserving embedding for facial expression recognition (Q716379) (← links)
• A survey of multilinear subspace learning for tensor data (Q716383) (← links)
• Twist tensor total variation regularized-reweighted nuclear norm based tensor completion for video missing area recovery (Q781059) (← links)
• The theoretical analysis of GLRAM and its applications (Q856470) (← links)
• Matrix-pattern-oriented Ho--Kashyap classifier with regularization learning (Q869046) (← links)
• Compression of magnetohydrodynamic simulation data using singular value decomposition (Q870619) (← links)
• MSAFC: matrix subspace analysis with fuzzy clustering ability (Q894666) (← links)
• Sampling based succinct matrix approximation (Q930090) (← links)
• A minimum norm approach for low-rank approximations of a matrix (Q989119) (← links)
• Bilinear Lanczos components for fast dimensionality reduction and feature extraction (Q991249) (← links)
• On low-complexity approximation of matrices (Q1329962) (← links)
• Inexact and incremental bilinear Lanczos components algorithms for high dimensionality reduction and image reconstruction (Q1677031) (← links)
• Prediction of protein-protein interactions by label propagation with protein evolutionary and chemical information derived from heterogeneous network (Q1705240) (← links)
• Incremental tensor principal component analysis for handwritten digit recognition (Q1719207) (← links)
• Factor models for matrix-valued high-dimensional time series (Q1739643) (← links)
• Matrix completion under interval uncertainty (Q1752160) (← links)
• Separable linear discriminant analysis (Q1927211) (← links)
• Weighted Moore-Penrose inverses of arbitrary-order tensors (Q1983772) (← links)
• Low-rank approximations for computing observation impact in 4D-Var data assimilation (Q2013720) (← links)
• A novel semi-supervised support vector machine with asymmetric squared loss (Q2036148) (← links)
• Ensemble learning-based computational imaging method for electrical capacitance tomography (Q2174712) (← links)
• Enhanced image approximation using shifted rank-1 reconstruction (Q2176516) (← links)
• Effective implementation to reduce execution time of a low-rank matrix approximation problem (Q2231284) (← links)
• Least upper bound of truncation error of low-rank matrix approximation algorithm using QR decomposition with pivoting (Q2231598) (← links)
• Marginface: A novel face recognition method by average neighborhood margin maximization (Q2270758) (← links)
• The generalized degrees of freedom of multilinear principal component analysis (Q2274928) (← links)
• Transformed rank-1 lattices for high-dimensional approximation (Q2303354) (← links)
• Novel alternating update method for low rank approximation of structured matrices (Q2402571) (← links)
• 1D-LDA vs. 2D-LDA: When is vector-based linear discriminant analysis better than matrix-based? (Q2427343) (← links)
• On optimality of approximate low rank solutions of large-scale matrix equations (Q2454151) (← links)
• Structured low rank approximation of a Bezout matrix (Q2468365) (← links)
• Comments on ``An analytical algorithm for generalized low-rank approximations of matrices'' (Q2476983) (← links)
• Optimal regularized low rank inverse approximation (Q2512812) (← links)
• An analytical algorithm for generalized low-rank approximations of matrices (Q2568089) (← links)
• Low-Rank Matrix Approximations Do Not Need a Singular Value Gap (Q3119542) (← links)
• Fast low rank approximations of matrices and tensors (Q3165168) (← links)
• (Q3447170) (← links)
• A Scalable Kernel-Based Semisupervised Metric Learning Algorithm with Out-of-Sample Generalization Ability (Q3536236) (← links)
• Real-Valued, Low Rank, Circulant Approximation (Q4443764) (← links)
• Literature survey on low rank approximation of matrices (Q4603753) (← links)
• Approximation Schemes for Low-rank Binary Matrix Approximation Problems (Q4973060) (← links)
• Why Are Big Data Matrices Approximately Low Rank? (Q5025778) (← links)