Lossless prioritized embeddings

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Given metric spaces (X, d) and (Y, ρ) and an ordering x1, x2, . . ., xn of (X, d), an embedding f : X → Y is said to have a prioritized distortion α(·), for a function α(·), if for any pair xj, x0 of distinct points in X, the distortion provided by f for this pair is at most α(j). If Y is a normed space, the embedding is said to have prioritized dimension β(·), if f(xj) may have at most β(j) nonzero coordinates. The notion of prioritized embedding was introduced by Filtser and the current authors in [EFN18], where a rather general methodology for constructing such embeddings was developed. Though this methodology enabled [EFN18] to come up with many prioritized embeddings, it typically incurs some loss in the distortion. In other words, in the worst-case, prioritized embeddings obtained via this methodology incur distortion which is at least a constant factor off, compared to the distortion of the classical counterparts of these embeddings. This constant loss is problematic for isometric embeddings. It is also troublesome for Matousek's embedding of general metrics into l, which for a parameter k = 1, 2, . . ., provides distortion 2k−1 and dimension O(k log n·n1/k). In this paper we devise two lossless prioritized embeddings. The first one is an isometric prioritized embedding of tree metrics into l with dimension O(log j), matching the worst-case guarantee of O(log n) of the classical embedding of Linial et al. [LLR95]. The second one is a prioritized Matousek's embedding of general metrics into l, which for a parameter k = 1, 2, . . ., provides prioritized distortion 2dk loglognj e− 1 and dimension O(k log n · n1/k), again matching the worst-case guarantee 2k − 1 in the distortion of the classical Matousek's embedding. We also provide a dimension-prioritized variant of Matousek's embedding. Finally, we devise prioritized embeddings of general metrics into (single) ultra-metric and of general graphs into (single) spanning tree with asymptotically optimal distortion.

Original languageEnglish
Title of host publication31st Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2020
EditorsShuchi Chawla
PublisherAssociation for Computing Machinery
Pages1049-1062
Number of pages14
ISBN (Electronic)9781611975994
StatePublished - 1 Jan 2020
Event31st Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2020 - Salt Lake City, United States
Duration: 5 Jan 20208 Jan 2020

Publication series

NameProceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms
Volume2020-January

Conference

Conference31st Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2020
Country/TerritoryUnited States
CitySalt Lake City
Period5/01/208/01/20

ASJC Scopus subject areas

  • Software
  • General Mathematics

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