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1
vote
Anti-concentration inequality for the eigenvalue of Gaussian matrix
Theorem 2 in
Iain M. Johnstone. Zongming Ma. "Fast approach to the Tracy–Widom law at the edge of GOE and GUE." Ann. Appl. Probab. 22 (5) 1962 - 1988, October 2012. https://doi.org/10.1214/11-AAP819
…
0
votes
What is the limiting marginal distribution of a fixed number of coordinates of a random poin...
You can deduce the result if it is already known that $X_1\to^d N(0,1)$.
The convergence in law of $(X_1,...,X_k)$ boils down, for fixed reals $t_1,...,t_k$, to the convergence of the characteristic f …
3
votes
Example where concentration of measure fails nontrivially
$Y_i\sim^\text{iid} \text{Exp}(1)$ random variables, $f(Y)=\min_i Y_i$ has Exponential distribution with parameter $n$ with $f$ 1-Lipschitz. Then
$E[f(Y)]=1/n$ but
$$P(f(Y)-E[f(Y)]>t)=\exp(-n(t+1/n))$ …
1
vote
Concentration bounds for sums of random variables of permutations
The paper
Chao, C., Bai, Z., & Liang, W. (1993). Asymptotic Normality for Oscillation of Permutation. Probability in the Engineering and Informational Sciences, 7(2), 227-235. doi:10.1017/S0269964800 …
1
vote
On the invertibility of $Z^\top Z$, where $Z$ is a Random matrix with concentrated weakly co...
At step $k$, we pick two indies $i\ne j\in [n]$ (say, wlog, $i$ is picked first, then $j$) and the probability that $i$ has been picked before at least once at steps $1,...,k-1$ is at most
$$
\frac{2( …
1
vote
Accepted
Sub-Gaussian random variables and convex ordering
If $Z\sim N(0,1)$ and $X$ is subgaussian with subgaussian norm less than $1/\sqrt 2$ then
$$P(|X|>t)\le 2 e^{-t^2} \le K P(|Z|>t)
$$
for some numerical constant $K>1$, thanks to lower bound on $P(Z>t) …
1
vote
Accepted
Limiting value of $\dfrac{1_n^\top B^{-1} A B^{-1} 1_n}{d}$, where $A=WW^\top + a I_n$, $B =...
The distribution of $v^TB^{-1}AB^{-1}v$ is the same for every vector $v$ in the unit sphere either deterministic or independent of $W$. Once this is established, you are allowed to take $v=z/\|z\|$ in …
1
vote
Accepted
Normalized concentration inequality for empirical CDF (iid sum)
If $F(t)=1/n$, the Poisson/binomial approximation gives that $Y_n = nF_n(t)$ is Binomial($n,\frac1n$) and converges to Poisson(1), say in total variation distance. In particular, $P(Y_n=0)=P(F_n(t)=0) …
4
votes
Accepted
Beating the $1/\sqrt n$ rate of uniform-convergence over a linear function class
It is not possible to get $|\frac1n\sum_i z_i(w) - E[z_i(w)]|=O_P(r_n)$ with $r_n \lll n^{-1/2}$ even for a single $w$, since it would contradict the CLT whenever Var$[z_i(w)]>0$.