# Tag Info

### Approximating the sign rank of a matrix

Recent work by Alon, Moran, and Yehudayoff gives an $O(n/\log n)$ approximation algorithm. Let $d$ be the VC-dimension of a sign matrix $S$. The idea is that there exists an efficiently computable ...

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Accepted

### About learning a single Gaussian in total-variation distance

Essentially, this follows from three facts: learning a Gaussian in total variation distance $\delta$ is equivalent to learning its two parameters, $\mu,\Sigma$, to (respectively) $\ell_2$ and ...
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### Reference Request: Computational Learning Theory

I have a list of references (incomplete) that may interest you: https://kiranvodrahalli.github.io/links/#resources-notes-textbooks-monographs-classes-etc (second all the existing suggestions).
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This seems to be addressed in the following paper by Joseph P. Romano, Section 3 [1] (specifically, Example 1): Example 1 (Finite versus not finite mean). Let $X$ be $X_1, \dots, X_n$, $n$ i.i.d. ...