Sepehr Assadi - A Simple $(1-ε)$-Approximation Semi-Streaming Algorithm for Maximum (Weighted) Matching

theoretics:13451 - TheoretiCS, August 1, 2025, Volume 4 - https://doi.org/10.46298/theoretics.25.16
A Simple $(1-ε)$-Approximation Semi-Streaming Algorithm for Maximum (Weighted) MatchingArticle

Authors: Sepehr Assadi ORCID

We present a simple semi-streaming algorithm for $(1-ε)$-approximation of bipartite matching in $O(\log{\!(n)}/ε)$ passes. This matches the performance of state-of-the-art "$ε$-efficient" algorithms -- the ones with much better dependence on $ε$ albeit with some mild dependence on $n$ -- while being considerably simpler.
The algorithm relies on a direct application of the multiplicative weight update method with a self-contained primal-dual analysis that can be of independent interest. To show case this, we use the same ideas, alongside standard tools from matching theory, to present an equally simple semi-streaming algorithm for $(1-ε)$-approximation of weighted matchings in general (not necessarily bipartite) graphs, again in $O(\log{\!(n)}/ε)$ passes.

25 pages. This is the TheoretiCS journal version


Volume: Volume 4
Published on: August 1, 2025
Accepted on: February 7, 2025
Submitted on: April 23, 2024
Keywords: Data Structures and Algorithms, Distributed, Parallel, and Cluster Computing
Funding:
    Source : OpenAIRE Graph
  • CAREER: Graph Streaming, Communication Games, and the Quest for Optimal Algorithms; Funder: National Science Foundation; Code: 2047061

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