Approximating Dynamic Time Warping Distance Between Run-Length Encoded Strings

Authors Zoe Xi, William Kuszmaul



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Zoe Xi
  • Massachusetts Institute of Technology, Cambridge, MA, USA
William Kuszmaul
  • Massachusetts Institute of Technology, Cambridge, MA, USA

Acknowledgements

The authors would like to thank Charles E. Leiserson for his helpful feedback and suggestions.

Cite As Get BibTex

Zoe Xi and William Kuszmaul. Approximating Dynamic Time Warping Distance Between Run-Length Encoded Strings. In 30th Annual European Symposium on Algorithms (ESA 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 244, pp. 90:1-90:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022) https://doi.org/10.4230/LIPIcs.ESA.2022.90

Abstract

Dynamic Time Warping (DTW) is a widely used similarity measure for comparing strings that encode time series data, with applications to areas including bioinformatics, signature verification, and speech recognition. The standard dynamic-programming algorithm for DTW takes O(n²) time, and there are conditional lower bounds showing that no algorithm can do substantially better. 
In many applications, however, the strings x and y may contain long runs of repeated letters, meaning that they can be compressed using run-length encoding. A natural question is whether the DTW-distance between these compressed strings can be computed efficiently in terms of the lengths k and 𝓁 of the compressed strings. Recent work has shown how to achieve O(k𝓁² + 𝓁 k²) time, leaving open the question of whether a near-quadratic Õ(k𝓁)-time algorithm might exist.
We show that, if a small approximation loss is permitted, then a near-quadratic time algorithm is indeed possible: our algorithm computes a (1 + ε)-approximation for DTW(x, y) in Õ(k𝓁 / ε³) time, where k and 𝓁 are the number of runs in x and y. Our algorithm allows for DTW to be computed over any metric space (Σ, δ) in which distances are O(log n)-bit integers. Surprisingly, the algorithm also works even if δ does not induce a metric space on Σ (e.g., δ need not satisfy the triangle inequality).

Subject Classification

ACM Subject Classification
  • Theory of computation → Approximation algorithms analysis
Keywords
  • Dynamic time warping distance
  • approximation algorithms
  • run-length encodings
  • computational geometry

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