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Algorithms
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Algorithms
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Algorithms
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https://dx.doi.org/10.48550/ar...
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Compressed Communication Complexity of Hamming Distance

Authors: Shiori Mitsuya; Yuto Nakashima 0001; Shunsuke Inenaga; Hideo Bannai; Masayuki Takeda;

Compressed Communication Complexity of Hamming Distance

Abstract

We consider the communication complexity of the Hamming distance of two strings. Bille et al. [SPIRE 2018] considered the communication complexity of the longest common prefix (LCP) problem in the setting where the two parties have their strings in a compressed form, i.e., represented by the Lempel-Ziv 77 factorization (LZ77) with/without self-references. We present a randomized public-coin protocol for a joint computation of the Hamming distance of two strings represented by LZ77 without self-references. Although our scheme is heavily based on Bille et al.’s LCP protocol, our complexity analysis is original which uses Crochemore’s C-factorization and Rytter’s AVL-grammar. As a byproduct, we also show that LZ77 with/without self-references are not monotonic in the sense that their sizes can increase by a factor of 4/3 when a prefix of the string is removed.

Keywords

FOS: Computer and information sciences, Industrial engineering. Management engineering, QA75.5-76.95, T55.4-60.8, Computational Complexity (cs.CC), Lempel-Ziv compression, <i>Hamming distance</i>, Computer Science - Computational Complexity, Hamming distance, Electronic computers. Computer science, Computer Science - Data Structures and Algorithms, communication complexity, Data Structures and Algorithms (cs.DS)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Top 10%
Average
Top 10%
Green
gold