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In the DSPOVX subroutine the symmetric positive definite matrix A is scaled if (among other criteria) the ratio between the smallest and the largest element of the main diagonal is `min(A(i,i))/max(A(…
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Is there a way to constrain the matrices while EM fitting?
For example- I want the transition matrix to be diagonal matrix, and the diagonal terms to be 0-1, like the below:
[[0.5 0 0]
[0 0.9 0]
…
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# 🐛 Bug
Using Deep Kernel Learning with the `InducingPointKernel` produces a non-positive-definite covariance matrix on test data (not the training data). The issue appears after the DNN weights + …
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I tried to get the pivoted Cholesky factorization of a positive semidefinite matrix using
```
C = cholesky(diagm([1, 0]), Val(true))
```
However this throws `RankDeficientException(1)`, even thoug…
olof3 updated
4 years ago
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I am interested in the generalized eigenvalue problem
`Hx=\lambda Mx`
where H is symmetric positive definite (and complex in general) but M is symmetric indefinite, i.e., it has negative eigenvalue…
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When working on matrix recovery problems, often a more generic low-rank matrix is thought after than the currently implemented symmetric positive semi-definite matrix. Could someone implement one of t…
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Hello,
How does LAMG compares to MATLAB's solvers ([`mldivide`](http://www.mathworks.com/help/matlab/ref/mldivide.html) and [`pcg`](http://www.mathworks.com/help/matlab/ref/pcg.html)) in performance?
…
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I keep getting this error if I try to use type="mixed".
> fit_oc
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Cholesky decomposition only works for positive definite matrices (AFAIK extensions of the Cholesky algorithms for positive semi-definite do exist also). Ironically, a very fast way to test whether a m…
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## 🚀 Feature
When working with large matrices, it's useful to access one or a handful of desired eigenpairs without computing the complete spectrum. PyTorch currently offers only `torch.lobpcg`, wh…