Preprint · July 9, 2026
Suppose we observe two sets of $n$ Gaussian vectors in $\mathbb{R}^d$, with the promise that, after applying a permutation of $[n]$ and a rotation of $\mathbb{R}^d$, the two sets are $ρ$-correlated. The Procrustes matching problem asks us to recover the un ...
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Preprint · July 2, 2026
A random geometric graph (RGG) is generated by first sampling latent points $x_1,\ldots,x_n$ independently and uniformly from the unit sphere in $\mathbb{R}^d$, and then connecting each pair $(i,j)$ if $\langle x_i,x_j\rangle$ exceeds some threshold $τ$. W ...
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Preprint · March 18, 2025
We revisit the classical broken sample problem: Two samples of i.i.d.\ data points ${\mathbf{X}}=\{X_{1},\ldots , X_{n}\}$ and ${\mathbf{Y}}=\{Y_{1},\ldots ,Y_{m}\}$ are observed without correspondence with $m\leq n$. Under the null hypothesis, ${\mathbf{X ...
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