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Locally Optimal Block Preconditioned Conjugate Gradient (LOBPCG) is a matrix-free method for finding the largest (or smallest) eigenvalues and the corresponding eigenvectors of a symmetric generalized eigenvalue problem
Applications, General software implementations & Overview
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eigenvalue displaystyle method block eigenvectors matrix rayleigh convergence iterative preconditioned gradient subspace eigenvector vectors version quotient every locally optimal single-vector
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| LOBPCG | related to Convergence theory and practice | Rayleigh | 0.60 | section |
| LOBPCG | related to Convergence theory and practice | Every | 0.60 | section |
| LOBPCG | related to Convergence theory and practice | Thus | 0.60 | section |
| LOBPCG | related to Convergence theory and practice | The | 0.60 | section |
| LOBPCG | related to Convergence theory and practice | For | 0.60 | section |
| LOBPCG | related to Convergence theory and practice | Moreover | 0.60 | section |
| LOBPCG | related to Convergence theory and practice | Gaussian | 0.60 | section |
| LOBPCG | related to Convergence theory and practice | To | 0.60 | section |
| LOBPCG | related to Data mining | Software | 0.60 | section |
| LOBPCG | related to Data mining | Megaman | 0.60 | section |
| LOBPCG | related to Data mining | Laplacian | 0.60 | section |
| LOBPCG | related to Data mining | NVIDIA | 0.60 | section |
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