A recent line of research termed" unlabeled sensing" and" shuffled linear regression" has
been exploring under great generality the recovery of signals from subsampled and …

A tacit assumption in linear regression is that (response, predictor)-pairs correspond to
identical observational units. A series of recent works have studied scenarios in which this …

The assumption that response and predictor belong to the same statistical unit may be
violated in practice. Unbiased estimation and recovery of true label ordering based on …

A recent unlabeled sampling result by Unnikrishnan, Haghighatshoar, and Vetterli states
that with probability one over Gaussian random matrices A with iid entries, any x can be …

We consider a regression problem, where the correspondence between input and output
data is not available. Such shuffled data is commonly observed in many real world …

摘要 Given two endomorphisms τ1, τ2 of ℂm, we provide eigenspace conditions under
which τ1 (v1)= τ2 (v2) for v1, v2∈ can only be true if v1= v2, where is a general n …

Towards low-latency communication for short-packet transmission, this paper tackles the
problem of shuffled linear regression for large-scale wireless sensor networks with header …

Linear regression with shuffled labels is the problem of performing a linear regression fit on
datasets whose labels are unknowingly shuffled with respect to their inputs. Such a problem …

Identification of matching records in multiple files can be a challenging and error-prone task.
Linkage error can considerably affect subsequent statistical analysis based on the resulting …

In the analysis of data sets consisting of (X, Y)-pairs, a tacit assumption is that each pair
corresponds to the same observational unit. If, however, such pairs are obtained via record …