Faster Maxflow via Improved Dynamic Spectral Vertex Sparsifiers
Abstract
We make several advances broadly related to the maintenance of electrical flows in weighted graphs undergoing dynamic resistance updates, including: 1. More efficient dynamic spectral vertex sparsification, achieved by faster length estimation of random walks in weighted graphs using Morris counters [Morris 1978, Nelson-Yu 2020]. 2. A direct reduction from detecting edges with large energy in dynamic electric flows to dynamic spectral vertex sparsifiers. 3. A procedure for turning algorithms for estimating a sequence of vectors under updates from an oblivious adversary to one that tolerates adaptive adversaries via the Gaussian-mechanism from differential privacy. Combining these pieces with modifications to prior robust interior point frameworks gives an algorithm that on graphs with edges computes a mincost flow with edge costs and capacities in in time . In prior and independent work, [Axiotis-M\k{a}dry-Vladu FOCS 2021] also obtained an improved algorithm for sparse mincost flows on capacitated graphs. Our algorithm implies a time maxflow algorithm, improving over the time maxflow algorithm of [Gao-Liu-Peng FOCS 2021].
Keywords
Cite
@article{arxiv.2112.00722,
title = {Faster Maxflow via Improved Dynamic Spectral Vertex Sparsifiers},
author = {Jan van den Brand and Yu Gao and Arun Jambulapati and Yin Tat Lee and Yang P. Liu and Richard Peng and Aaron Sidford},
journal= {arXiv preprint arXiv:2112.00722},
year = {2021}
}
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63 pages