Hidden Permutations to the Rescue: Multi-Pass Semi-Streaming Lower Bounds for Approximate Matchings
Sepehr Assadi, Janani Sundaresan

TL;DR
This paper establishes new lower bounds for semi-streaming algorithms approximating maximum bipartite matchings, using novel permutation compression techniques and group theory, addressing a longstanding open problem.
Contribution
It introduces a new hardness amplification method for permutations via concatenation, advancing lower bounds in semi-streaming matching approximation.
Findings
Proves lower bounds depending on the parameter eta for semi-streaming algorithms.
First pass-approximation lower bounds for constant matchings in semi-streaming.
Develops permutation compression techniques using group representation theory.
Abstract
We prove that any semi-streaming algorithm for -approximation of maximum bipartite matching requires \[ \Omega(\frac{\log{(1/\epsilon)}}{{\log{(1/\beta)}}}) \] passes, where is the largest parameter so that an -vertex graph with edge-disjoint induced matchings of size exist (such graphs are referred to as RS graphs). Currently, it is known that \[ \Omega(\frac{1}{\log\log{n}}) \leqslant \beta \leqslant 1-\Theta(\frac{\log^*{n}}{{\log{n}}}) \] and closing this huge gap between upper and lower bounds has remained a notoriously difficult problem in combinatorics. Under the plausible hypothesis that , our lower bound result provides the first pass-approximation lower bound for (small) constant approximation of matchings in the semi-streaming model, a longstanding open question in the graph streaming literature.…
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Taxonomy
TopicsCaching and Content Delivery · Cooperative Communication and Network Coding · Complexity and Algorithms in Graphs
