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Tree trace reconstruction using subtraces

Publication ,  Journal Article
Brailovskaya, T; Rácz, MZ
Published in: Journal of Applied Probability
January 1, 2023

Tree trace reconstruction aims to learn the binary node labels of a tree, given independent samples of the tree passed through an appropriately defined deletion channel. In recent work, Davies, Rácz, and Rashtchian [10] used combinatorial methods to show that exp (O(k logk n)) samples suffice to reconstruct a complete k-ary tree with n nodes with high probability. We provide an alternative proof of this result, which allows us to generalize it to a broader class of tree topologies and deletion models. In our proofs we introduce the notion of a subtrace, which enables us to connect with and generalize recent mean-based complex analytic algorithms for string trace reconstruction.

Duke Scholars

Published In

Journal of Applied Probability

DOI

ISSN

0021-9002

Publication Date

January 1, 2023

Volume

60

Issue

2

Start / End Page

629 / 641

Related Subject Headings

  • Statistics & Probability
  • 4905 Statistics
  • 4901 Applied mathematics
  • 0104 Statistics
  • 0102 Applied Mathematics
 

Citation

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Brailovskaya, T., & Rácz, M. Z. (2023). Tree trace reconstruction using subtraces. Journal of Applied Probability, 60(2), 629–641. https://doi.org/10.1017/jpr.2022.81
Brailovskaya, T., and M. Z. Rácz. “Tree trace reconstruction using subtraces.” Journal of Applied Probability 60, no. 2 (January 1, 2023): 629–41. https://doi.org/10.1017/jpr.2022.81.
Brailovskaya T, Rácz MZ. Tree trace reconstruction using subtraces. Journal of Applied Probability. 2023 Jan 1;60(2):629–41.
Brailovskaya, T., and M. Z. Rácz. “Tree trace reconstruction using subtraces.” Journal of Applied Probability, vol. 60, no. 2, Jan. 2023, pp. 629–41. Scopus, doi:10.1017/jpr.2022.81.
Brailovskaya T, Rácz MZ. Tree trace reconstruction using subtraces. Journal of Applied Probability. 2023 Jan 1;60(2):629–641.
Journal cover image

Published In

Journal of Applied Probability

DOI

ISSN

0021-9002

Publication Date

January 1, 2023

Volume

60

Issue

2

Start / End Page

629 / 641

Related Subject Headings

  • Statistics & Probability
  • 4905 Statistics
  • 4901 Applied mathematics
  • 0104 Statistics
  • 0102 Applied Mathematics