Suppose that we have a regression problem with response variable $ Y\in\mathbb {R}^ d $
and predictor $ X\in\mathbb {R}^ d $, for $ d\ge 1$. In permuted or unlinked regression we …

This paper studies the problem of matching two complete graphs with edge weights
correlated through latent geometries, extending a recent line of research on random graph …

Consider a noisy linear observation model with an unknown permutation, based on
observing y= Π* Ax*+ w, where x*∈ ℝ d is an unknown vector, Π* is an unknown nxn …

Neural networks trained with stochastic gradient descent (SGD) starting from different
random initialisations typically find functionally very similar solutions, raising the question of …

In regression analysis of multivariate data, it is tacitly assumed that response and predictor
variables in each observed response-predictor pair correspond to the same entity or unit. In …

NMR chemical shift changes can report on the functional dynamics of biomacromolecules in
solution with sizes> 1 MDa. However, their interpretation requires chemical shift …

Isotonic regression with unknown permutations: Statistics, computation and adaptation Page 1
The Annals of Statistics 2022, Vol. 50, No. 1, 324–350 https://doi.org/10.1214/21-AOS2107 © …

The supplement [10] includes all the technical proofs. In Appendix A, we first give the proof
of Theorem 3.1. In Appendix B, we give the proof of Theorem 4.1. After that, we prove …

Optimal rates of statistical seriation Page 1 Bernoulli 25(1), 2019, 623–653 https://doi.org/10.3150/17-BEJ1000
Optimal rates of statistical seriation NICOLAS FLAMMARION1, CHENG MAO2,* and …

Unlabeled linear regression, or “linear regression with an unknown permutation”, has
attracted increasing attentions due to its applications in (eg,) linkage record and de …