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In linear algebra, the Gram matrix (or Gramian matrix, Gramian) of vectors v 1 , … , v n {\displaystyle v_{1},\dots ,v_{n}} in an inner product space is the Hermitian matrix of inner products, whose entries are given by the inner product G i j = ⟨ v i , v j ⟩ {\displaystyle G_{ij}=\left\langle v_{i},v_{j}\right\rangle } . If the vectors v 1 , … , v n…
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| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Gram matrix | is a | singular value decomposition | 0.90 | text |
| Gram matrix | has application | In Riemannian | 0.60 | section |
| Gram matrix | has application | Riemannian | 0.60 | section |
| Gram matrix | has application | Gramian | 0.60 | section |
| Gram matrix | has application | This | 0.60 | section |
| Gram matrix | has application | If | 0.60 | section |
| Gram matrix | has application | In | 0.60 | section |
| Gram matrix | has application | Gram | 0.60 | section |
| Gram matrix | has application | Jamshidian | 0.60 | section |
| Gram matrix | has application | Bentler | 0.60 | section |
| Gram matrix | has application | Applied Psychological Measurement | 0.60 | section |
| Gram matrix | has application | Volume | 0.60 | section |
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