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Triangle and Four Cycle Counting in the Data Stream Model

Summary: Improved algorithms and matching lower bounds for triangle and 4‑cycle counting across arbitrary-, random-, and adjacency-list-order streams, yielding strictly better space/pass trade-offs. Highlights: single-pass (1+ε) triangles in random-order (optimal), adjacency-list single-pass/density 4‑cycle guarantees, and multi-/one-pass improvements and lower bounds for 4‑cycles in arbitrary order. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1783
Venue
PODS
Year
2020
Pagerank
4.9050236e-05
Overall Rank
6,864 | 52.25%
DOI
10.1145/3375395.3387652

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Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
10,342 An Improved Fully Dynamic Algorithm for Counting 4-Cycles in General Graphs Using Fast Matrix Multiplication 2025 PODS 4.1945683e-05
10,596 Truss Decomposition in Hypergraphs 2025 VLDB 4.1945683e-05
11,321 Approximately Counting Subgraphs in Data Streams 2022 PODS 4.1945683e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 7 of 7 cited papers.

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

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