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How the Degeneracy Helps for Triangle Counting in Graph Streams

Summary: Constant-pass streaming algorithm for (1±ε)-triangle counting with space O(m·κ/T), leveraging graph degeneracy κ to significantly improve upon prior m^{3/2}/T and m/√T bounds for low-degeneracy families (e.g., planar, minor-closed, preferential-attachment). Proven nearly-matching lower bound Ω(m·κ/T). (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1796
Venue
PODS
Year
2020
Pagerank
4.4937074e-05
Overall Rank
8,533 | 40.64%
DOI
10.1145/3375395.3387665

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Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
11,321 Approximately Counting Subgraphs in Data Streams 2022 PODS 4.1945683e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 3 of 3 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
392 Counting Triangles in Data Streams 2006 PODS 0.00024556183
1,344 Counting and Sampling Triangles from a Graph Stream 2013 VLDB 0.00012473724
5,046 Better Algorithms for Counting Triangles in Data Streams 2016 PODS 5.7405307e-05
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