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Theory and applications of probability and stochastic processes: e.g. central limit theorems, large deviations, stochastic differential equations, models from statistical mechanics, queuing theory.
234
votes
Accepted
What is convolution intuitively?
I remember as a graduate student that Ingrid Daubechies frequently referred to convolution by a bump function as "blurring" - its effect on images is similar to what a short-sighted person experiences …
62
votes
Accepted
Why is the Gaussian so pervasive in mathematics?
Quadratic (or bilinear) forms appear naturally throughout mathematics, for instance via inner product structures, or via dualisation of a linear transformation, or via Taylor expansion around the line …
43
votes
Accepted
Anti-concentration bound for permanents of Gaussian matrices?
I did a preliminary feasibility analysis of our methods and it appears possible that one may be able to tighten our $n^\epsilon$ loss to something more like $\exp( \sqrt{n} )$ in the Gaussian case, bu …
38
votes
If $X$ and $Y$ independent and identically distributed, then $E(|X-Y|)\leq E(|X+Y|)$. Are ot...
Shorn of probabilistic language, this inequality follows from the assertion that $|x+y|-|x-y|$ is a positive semi-definite kernel, and is therefore the sum (or integral) of squares. Your Fourier-anal …
33
votes
Accepted
Random sequence of integers in $\{1, 2, \dots, n \}$ which is "everywhere probably increasin...
I adapt an argument from this blog post of mine, exploiting the $\ell^2$ boundedness of the discrete Hilbert transform (i.e. Hilbert's inequality), to obtain an exponential upper bound. I don't see a …
30
votes
Accepted
"Entropy" proof of Brunn-Minkowski Inequality?
The similarity between the entropy power inequality and the Brunn-Minkowski inequality is not directly related to convexity - after all, Brunn-Minkowski can be generalised to bounded open sets that ar …
28
votes
Accepted
Is there a noncommutative Gaussian?
The theory of classical independence and classical convolution can be generalised to noncommutative settings in several ways. The most famous one is that of free independence and free convolution (int …
24
votes
Accepted
Why is free probability a generalization of probability theory?
Quite a lot of questions here!
It is perhaps worth making a distinction between scalar classical probability theory - the study of scalar classical random variables - and more general classical proba …
24
votes
Accepted
Intuitive understanding of the Stieltjes transform
Firstly, the equation you attribute to Silverstein (and is sometimes known as the "self-consistent equation" for the Stieltjes transform) is not exact, but only asymptotically valid in the limit $n \t …
21
votes
Can random variables that almost surely solve equations be repaired to surely solve these eq...
After chasing down references relating to the paper of Shelah mentioned by Will Brian, I now have a satisfactory answer to the question. It all hinges on whether there is a splitting of the quotient …
20
votes
Accepted
Choosing a relative large density subsequence from a low density sequence
The answer is no.
This is a good illustration of a reasoning principle identified explicitly in
Gowers, W. T., The two cultures of mathematics, Arnold, V. (ed.) et al., Mathematics: Frontiers and pers …
19
votes
Heuristic lower bounds on small sums of roots of unity
One heuristic is to replace the $n^{th}$ roots of unity by $n$ iid elements $\zeta_1,\dots,\zeta_n$ of the unit circle, drawn uniformly at random. For any sum $\zeta_{i_1} + \dots + \zeta_{i_k}$ of $ …
16
votes
Accepted
Some models for random graphs that I am curious about
The Lovasz-Szegedy theory of graphons is likely to be relevant. Every measurable symmetric function $p: [0,1] \times [0,1] \to [0,1]$ (otherwise known as a graphon) determines a random graph model, i …
16
votes
Accepted
Probability vector $p$ majorizes its normalized entropy vector $\small \frac{-p\log p}{H(p)}$
This appears to be the case, but I was forced to rely on a somewhat complicated inequality on two real variables that looks quite plausible numerically, though I do not have a 100% rigorous proof of i …
15
votes
Accepted
When does a pointwise CLT hold?
Bounded density will suffice, I think. Basically what one needs is for the Fourier transforms (aka characteristic functions) of the $X_1 + \ldots + X_n / \sqrt{n}$ to converge pointwise to the Fourie …