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20182022
most citedEfficient average-case population recovery in the presence of insertions and deletions

4 citations · 6 across the 4 of their papers we have counts for

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cs.DS2022

Approximate Trace Reconstruction from a Single Trace

Xi Chen, Anindya De, Chin Ho Lee +2

The well-known trace reconstruction problem is the problem of inferring an unknown source string from independent "traces", i.e. copies of that have been corr…

cs.DS2021

Near-Optimal Average-Case Approximate Trace Reconstruction from Few Traces

Xi Chen, Anindya De, Chin Ho Lee +2

In the standard trace reconstruction problem, the goal is to \emph{exactly} reconstruct an unknown source string from independent "traces", which are cop…

cs.DS2020

Polynomial-time trace reconstruction in the low deletion rate regime

Xi Chen, Anindya De, Chin Ho Lee +2

In the \emph{trace reconstruction problem}, an unknown source string is transmitted through a probabilistic \emph{deletion channel} which independently deletes ea…

cs.DS20202 cited

Polynomial-time trace reconstruction in the smoothed complexity model

Xi Chen, Anindya De, Chin Ho Lee +2

In the \emph{trace reconstruction problem}, an unknown source string is sent through a probabilistic \emph{deletion channel} which independently deletes each bit…

cs.DS20194 cited

Efficient average-case population recovery in the presence of insertions and deletions

Frank Ban, Xi Chen, Rocco A. Servedio +1

Several recent works have considered the \emph{trace reconstruction problem}, in which an unknown source string is transmitted through a probabilistic channel which…

cs.DS2019

Beyond trace reconstruction: Population recovery from the deletion channel

Frank Ban, Xi Chen, Adam Freilich +2

\emph{Population recovery} is the problem of learning an unknown distribution over an unknown set of -bit strings, given access to independent draws from the distribution that h…