Approximate Fully Dynamic Directed Densest Subgraph
Richard Li, Kent Quanrud

TL;DR
This paper introduces a new fully dynamic algorithm for maintaining an approximate directed densest subgraph with improved update times, advancing the efficiency of dynamic graph algorithms.
Contribution
It presents the first algorithm achieving near-logarithmic amortized and worst-case update times for maintaining a $(1-\varepsilon)$-approximate directed densest subgraph.
Findings
Achieves $ ilde{O}(rac{ ext{log}^3(n)}{ extvarepsilon^6})$ amortized update time.
Achieves $ ilde{O}(rac{ ext{log}^4(n)}{ extvarepsilon^7})$ worst-case update time.
Improves upon previous algorithms with higher update time complexities.
Abstract
We give a fully dynamic algorithm maintaining a -approximate directed densest subgraph in amortized time or worst-case time per edge update (where hides factors), based on earlier work by Chekuri and Quanrud [arXiv:2210.02611, arXiv:2310.18146]. This result improves on earlier work done by Sawlani and Wang [arXiv:1907.03037], which guarantees worst case time for edge insertions and deletions.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAlgorithms and Data Compression · Complexity and Algorithms in Graphs · Machine Learning and Algorithms
