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Jun
30 |
accepted | Shared maximum eigenvector |
Jun
30 |
comment |
Shared maximum eigenvector
Could you elaborate your response a little? |
Jun
29 |
comment |
Shared maximum eigenvector
$A$, $B$ are only required to be Hermitian. With this, the eigenvalues are always real, then there are no worries about the ordering. |
Jun
29 |
comment |
Shared maximum eigenvector
Thank you Nik, I add the condition of A and B being Hermitian. I look for a more 'exhaustive' condition rather than the ones I metion in the question. |
Jun
29 |
revised |
Shared maximum eigenvector
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Jun
29 |
asked | Shared maximum eigenvector |
Jun
23 |
comment |
MLE and CRLB with mismatched likelihoods
I think that it is easy to observe what happens with the Fisher information (so as for the CRLB) when KL decomposition is used. |
Jun
4 |
accepted | Hadamard Product and Eigendecomposition |
May
29 |
revised |
Hadamard Product and Eigendecomposition
added 382 characters in body |
May
28 |
comment |
Hadamard Product and Eigendecomposition
OK, then I assume no further insights can be obtained. |
May
28 |
asked | Hadamard Product and Eigendecomposition |
Mar
23 |
comment |
Finding the optimal mixture of two convex functions
Whenever we have a more clear understanding of f(.), it is possible to re-write the problem somehow. For instance, if f is a linear form, the problem becomes a QCQP which can be approximately solved under certain conditions. |
Mar
20 |
comment |
Matrix inequality
Right, but I guess the ordering defined with arbitrary matrices is preserved. |
Mar
20 |
comment |
Matrix inequality
Nice derivation. Can I include you in the paper's acknowledgement ? |
Mar
20 |
accepted | Matrix inequality |
Mar
20 |
awarded | Curious |
Mar
19 |
asked | Matrix inequality |
Jan
29 |
accepted | Positive solutions of linear systems with a diagonally dominant matrix |
Jan
27 |
answered | What's the most efficient way to solve this euclidean projection on non-negative affine space constraint? |
Jan
14 |
revised |
Positive solutions of linear systems with a diagonally dominant matrix
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