Pages that link to "Item:Q2847729"

The following pages link to Limited memory block Krylov subspace optimization for computing dominant singular value decompositions (Q2847729):

Displaying 27 items.

• Accelerating large partial EVD/SVD calculations by filtered block Davidson methods (Q341332) (← links)
• Principal components: a descent algorithm (Q349019) (← links)
• Low-rank incremental methods for computing dominant singular subspaces (Q413537) (← 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)
• Subspace methods with local refinements for eigenvalue computation using low-rank tensor-train format (Q520189) (← links)
• A Riemannian conjugate gradient method for optimization on the Stiefel manifold (Q2012231) (← links)
• Efficient proximal mapping computation for low-rank inducing norms (Q2073049) (← links)
• Trace minimization method via penalty for linear response eigenvalue problems (Q2083411) (← links)
• Background subtraction using adaptive singular value decomposition (Q2217381) (← links)
• A brief introduction to manifold optimization (Q2218094) (← links)
• Preconditioners for nonsymmetric indefinite linear systems (Q2332746) (← links)
• Hierarchical optimization for neutron scattering problems (Q2375168) (← links)
• Research on the advances of the singular value decomposition and its application in high-dimensional data mining (Q2916882) (← links)
• The Singular Value Decomposition: Anatomy of Optimizing an Algorithm for Extreme Scale (Q4554900) (← links)
• (Q4583459) (← links)
• A New First-Order Algorithmic Framework for Optimization Problems with Orthogonality Constraints (Q4603042) (← links)
• TRPL+K: Thick-Restart Preconditioned Lanczos+K Method for Large Symmetric Eigenvalue Problems (Q4632005) (← links)
• Finding Low-Rank Solutions via Nonconvex Matrix Factorization, Efficiently and Provably (Q5230407) (← links)
• Structured Quasi-Newton Methods for Optimization with Orthogonality Constraints (Q5230652) (← links)
• Estimating a Few Extreme Singular Values and Vectors for Large-Scale Matrices in Tensor Train Format (Q5265006) (← links)
• Accelerating Convergence by Augmented Rayleigh--Ritz Projections For Large-Scale Eigenpair Computation (Q5346754) (← links)
• An Efficient Gauss--Newton Algorithm for Symmetric Low-Rank Product Matrix Approximations (Q5502244) (← links)
• Limited memory restarted \(\ell^p\)-\(\ell^q\) minimization methods using generalized Krylov subspaces (Q6038831) (← links)
• Stochastic Gauss-Newton algorithms for online PCA (Q6111665) (← links)
• Slow and finite-time relaxations to \(m\)-bipartite consensus on the Stiefel manifold (Q6174063) (← links)
• A tensor train approach for internet traffic data completion (Q6601544) (← links)
• Seeking consensus on subspaces in federated principal component analysis (Q6636797) (← links)