Abstract
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.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 629-641 |
| Number of pages | 13 |
| Journal | Journal of Applied Probability |
| Volume | 60 |
| Issue number | 2 |
| DOIs | |
| State | Published - 2023 |
All Science Journal Classification (ASJC) codes
- Statistics and Probability
- General Mathematics
- Statistics, Probability and Uncertainty
Keywords
- Trace reconstruction
- statistical error correction
- tree graphs
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