Dynamic Algorithms for Maximum Matching Size
Soheil Behnezhad

TL;DR
This paper improves dynamic algorithms for approximating maximum matching size, achieving better update times and approximation ratios when only the size of the matching is maintained, using novel connections to sublinear algorithms.
Contribution
It introduces new dynamic algorithms that improve approximation ratios and update times for maximum matching size, leveraging sublinear algorithms and a new characterization of tight instances.
Findings
Achieves a 0.501-approximation with polylogarithmic update time
Maintains a (2/3 + Ω(1))-approximation in O(√n) time for bipartite graphs
Develops a new characterization of tight instances for EDCS
Abstract
We study fully dynamic algorithms for maximum matching. This is a well-studied problem, known to admit several update-time/approximation trade-offs. For instance, it is known how to maintain a 1/2-approximate matching in update time or a -approximate matching in update time, where is the number of vertices. It has been a long-standing open problem to determine whether either of these bounds can be improved. In this paper, we show that when the goal is to maintain just the size of the matching (and not its edge-set), then these bounds can indeed be improved. First, we give an algorithm that takes update-time and maintains a -approximation (-approximation if the graph is bipartite). Second, we give an algorithm that maintains a -approximation in time for bipartite graphs. Our results…
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Videos
Recent Progress on Sublinear Time Algorithms for Maximum Matching: Upper Bounds· youtube
Taxonomy
TopicsComplexity and Algorithms in Graphs · Advanced Graph Theory Research · Optimization and Search Problems
