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seen Jul 24 at 17:13

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.
May
20
comment Computing volume of an ellipsoid with a cone about its major axis removed?
3d case is not so bad and specific equations for the cone are also not bad in this case
Mar
29
comment Simple question about inequality involving eigenvalue of a matrix and a scaled version of that matrix
It is fixed. Sorry for the typos.
Feb
7
comment mixture of multivariate Gaussians is elliptical?
Can you be specific? Maybe write an answer? The link you showed seemed to suggest that linear combinations of elliptical functions were elliptical. If this is true than my second question remains.
Feb
7
comment mixture of multivariate Gaussians is elliptical?
I think maybe your question was whether I was taking a convolution or a mixture. I am taking a mixture.
Feb
7
comment mixture of multivariate Gaussians is elliptical?
The point is that you are drawing with probability $p$ from one distribution, and with probability $(1-p)$ from the other distribution. As I understand it this is called a mixture distribution. So my first question is whether this mixture of Gaussians is elliptical (it cannot be Gaussian). And if so how can we express it explicitly by the definition of an elliptical distribution.
Feb
7
comment mixture of multivariate Gaussians is elliptical?
I don't understand the distinction, perhaps. We are drawing points/vectors from these distributions. I will shortly define elliptical distributions.
Feb
7
comment mixture of multivariate Gaussians is elliptical?
These are probability distribution. In particular they are en.wikipedia.org/wiki/Multivariate_normal_distribution
Oct
4
comment General question about matrix calculus with specific example (with attempted answer)
I already solved this example in my question. It was the general case ($p\neq 2$ that bothered me).
Oct
4
comment General question about matrix calculus with specific example (with attempted answer)
Yes, the last edit.
Oct
4
comment General question about matrix calculus with specific example (with attempted answer)
Thanks, this looks right. But then what is the flaw in my last argument for what the derivative should be?
Oct
4
comment General question about matrix calculus with specific example (with attempted answer)
Interesting. If you type that up as an answer, I can give you the bounty. No one else has taken a crack at it.
Sep
27
comment quick factorization of rank-one matrices (generally, and of a particular form)
D'oh! Why, of course. Thank you!
May
2
comment Inducing orientations on boundary manifolds
I don't understand your comment. It does not seem like you are addressing my question.
May
2
comment Inducing orientations on boundary manifolds
My whole question is about determining the sign of $dx$ here. And my question about $\omega$ applies in generality: $k$-form fields $\omega$ orient $k$-manifolds.
Apr
27
comment Probability that random vectors have a certain dot product
er, what i mean is that you are integrating with respect to the variable in the upper index. you need to make one of those variables different.
Apr
27
comment Probability that random vectors have a certain dot product
The upper index of your integral should be $\pi/2$, I think.