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seen Jun 18 at 21:52

PhD student in theoretical neuroscience and machine learning at Columbia


Sep
12
comment Scale invariance and the Mellin transform?
That must be the case being referred to when talking about the "scale-invariant" Mellin transform.
Sep
12
comment Scale invariance and the Mellin transform?
But that's a trivial case. Any transform of a scale-invariant function will be scale-invariant, by definition.
Sep
3
comment How are definitions of chaos related?
No, but I did come across the Pesin article they cite. It's well over my head though. Hopefully there is a good resource that covers the results from that article in a more accessible presentation.
Aug
13
comment Multilinear or Tensor Regression?
No - there is the difference between a linear map (a matrix) and a multilinear map (a higher-rank tensor), which is a kind of nonlinear map.
Jul
17
comment Algorithm for finding set of all parents recursively
Agreed. That's why I post things on math.SE :)
Jul
17
comment Algorithm for finding set of all parents recursively
Ah, I realize I was too general in what I was describing. I also want $A$ to have the property that there is no other set $B$ that contains all the parents of elements such that $A \subset B$. So in that case, you would first have to find the minimal elements of the graph, then apply this algorithm at those elements.
Jul
17
comment Algorithm for finding set of all parents recursively
Of course, one could brute force it. But there is probably something more elegant.
Jul
17
comment Algorithm for finding set of all parents recursively
Yes, that will find a set for one vertex. What about all?
Jul
17
comment Algorithm for finding set of all parents recursively
I suspect there is a graph theory term for what I'm trying to compute, but I am not aware of it. It's not the same as strongly connected components, although any strongly connected component should be a subset of the full set to be unioned.
Apr
10
comment Log likelihood of a realization of a Poisson process?
Unhelpful. Expectedly.
Apr
10
comment Log likelihood of a realization of a Poisson process?
Then enlighten me, good sir :p
Apr
10
comment Log likelihood of a realization of a Poisson process?
I upvoted before reading it fully. After going through it I realized that it did not answer my question, but only restated it with different notation (and as a probability instead of a log probability) so I undid my upvote. I feel that no vote would be a more appropriate response, but at this point my vote is locked in, and I figured someone with a reputation as high as yours would not be bothered by a single downvote (obviously I was wrong). If your answer did inspire my edit, it was only by confirming that there was no mistake in my derivation and that my confusion was coming from elsewhere.
Apr
10
comment Log likelihood of a realization of a Poisson process?
Punch in the face? Calm down. It's obviously a drop in the bucket of your otherwise sterling reputation. Take a few deep breaths and move on.
Mar
29
comment Log likelihood of a realization of a Poisson process?
Tried to undo it. But looking over it more closely, you didn't actually answer my question, you just restated it in a fancier way. I had a basic misunderstanding about stochastic processes that you didn't address.
Mar
28
comment Log likelihood of a realization of a Poisson process?
I'm still confused. It seems like your expression for $R^{s,N}_n(\mathbb{i})$ in the small $s$ limit is exactly the exponent of my expression for the discrete log likelihood in the small $\Delta t$ limit. What's different here?
Mar
21
comment Singular values of a diagonal matrix concatenated with a vector?
Interesting...how would I use that to get the singluar values?
Mar
21
comment Singular values of a diagonal matrix concatenated with a vector?
Yes, copper.hat and Git Gud are correct.
Mar
12
comment Fit a quadratic form given covariant derivatives
OK, so say we can solve for Q up to some constant factor on the diagonal. That means we could still solve for the eigenvectors of Q, right?
Mar
12
comment Fit a quadratic form given covariant derivatives
Right, it actually turns out to be almost trivial. Let $g = (I-xx^T)Qx$, let $h = (I-xx^T)Q(I-xx^T)-(x^TQx)(I-xx^T)$. You can expand $Q$ as $(I-xx^T)Q(I-xx^T) + xx^TQ(I-xx^T) + (I-xx^T)Qxx^T + xx^TQxx^t = h + xg^T + gx^T + f(x).$
Mar
8
comment Prove that there are no convex functions on compact manifolds
What about continuous but non-smooth functions?