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seen Dec 17 at 17:01

Dec
9
comment Norm of covariance and precision matrices: is there any meaning?
Good answer, but I am actually more interested in the precision matrix case.
Dec
6
comment Maximum entry of small-normed matrix
And I was referring to the spectral norm.
Dec
4
comment Are roots of a sparse matrix are sparse?
I didn't say anything about diagonal matrices.
Dec
2
comment Norm inequality question
I am not saying that we should have an equality, just some reasonable perturbation of this $\epsilon$, perhaps involving the norm of $T$.
Dec
1
comment “max” entry norm inequality?
For the 2 norm I think you need a factor of $\sqrt{n}$ in front of it, by the relationship of the 2 norm and infinity norm.
Dec
1
comment “max” entry norm inequality?
@AlgebraicPavel, the spectral norm. But perhaps a more sensible bound is a multiple of the infinity norm?
Nov
7
comment Covariance of a mixture of Gaussians
I mean can we say this is elliptical or something?
Nov
7
comment Covariance of a mixture of Gaussians
Thanks! Does this have a nice distribution, or is this all we can say?
Oct
8
comment Probability/Decision- infimum over set of expectations (can be interpreted as decision problem)
@whuber Btw, how is the second limit being zero implied by the assumption on the first moment of F being finite?
Oct
8
comment Solving integral related to second moment of normal distribution restricted to interval. CAS answer acceptable
That's not consistent with what you have about. Notice what happens if m is zero in your output.
Oct
7
comment Solving integral related to second moment of normal distribution restricted to interval. CAS answer acceptable
If m=0, everything cancels out and you get zero. Am I mistaken?
Oct
7
comment Solving integral related to second moment of normal distribution restricted to interval. CAS answer acceptable
If m is the mean, your answer says you have zero when m=0. That can't be.
Oct
7
comment Solving integral related to second moment of normal distribution restricted to interval. CAS answer acceptable
are you still in process? I see that both the last and second integrals are zero when the mean is zero. And then you are left with an integral which is the same as the first, in the case where the mean is zero.
Oct
7
comment Solving integral related to second moment of normal distribution restricted to interval. CAS answer acceptable
What are you calling m?
Oct
6
comment Probability/Decision- infimum over set of expectations (can be interpreted as decision problem)
Yes. It can be simplified a bit. But how to show that the right side reduces to the left...
Oct
6
comment Probability/Decision- infimum over set of expectations (can be interpreted as decision problem)
After what line?
May
22
comment Computing bottom $k$-eigenspace of a matrix via top $k$-eigenspace of another matrix
Yes, Will, I am indeed considering the absolute values of the eigenvalues. The problem with the inverse is that it is about as expensive as the full eigendecomposition.
May
22
comment Probability that one folded normal is bigger than another?
I would love to see your sketch.
May
22
comment Computing bottom $k$-eigenspace of a matrix via top $k$-eigenspace of another matrix
Why should the bottom eigenvectors of $R$ be the same here as the bottom eigenvectors of $S$?
May
22
comment Computing bottom $k$-eigenspace of a matrix via top $k$-eigenspace of another matrix
Thank you for your comment. You are right. I have modified the question to reflect my real wish, which is a matrix that is less expensive to compute than the full eigendecomposition or inverse.