Approximating Edit Distance in Near-Linear Time
Alexandr Andoni, Krzysztof Onak

TL;DR
This paper presents a near-linear time algorithm that approximates the edit distance between two strings within a factor of 2^{~O(sqrt(log n))}, significantly improving the efficiency over previous methods.
Contribution
It introduces the first sub-polynomial approximation algorithm for edit distance that operates in near-linear time, surpassing prior cubic-root approximation approaches.
Findings
Achieves approximation within a factor of 2^{~O(sqrt(log n))}
Runs in n^{1+o(1)} time, nearly linear
Improves upon previous n^{1/3+o(1)} approximation algorithms
Abstract
We show how to compute the edit distance between two strings of length n up to a factor of 2^{\~O(sqrt(log n))} in n^(1+o(1)) time. This is the first sub-polynomial approximation algorithm for this problem that runs in near-linear time, improving on the state-of-the-art n^(1/3+o(1)) approximation. Previously, approximation of 2^{\~O(sqrt(log n))} was known only for embedding edit distance into l_1, and it is not known if that embedding can be computed in less than quadratic time.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAlgorithms and Data Compression · Computational Geometry and Mesh Generation · Machine Learning and Algorithms
