On Asymptotic Cost of Triangle Listing in Random Graphs
Summary: Introduce a Glivenko–Cantelli–based stochastic framework to model in-memory triangle listing costs in random graph families; derive asymptotically exact CPU limits (n→∞) for all vertex/edge iterators under arbitrary acyclic orientations as closed-form functions of the degree distribution. Enables provable selection of optimal orientations and direct comparison of algorithm classes, identifying the best technique within each class. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Di Xiao
- 2. Yi Cui
- 3. Daren B. H. Cline
- 4. Dmitri Loguinov
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 11,331 | The Gibbs–Rand Model | 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 |
|---|---|---|---|---|
| 110 | On Triangulation-based Dense Neighborhood Graph Discovery | 2011 | VLDB | 0.00047892924 |
| 589 | Massive Graph Triangulation | 2013 | SIGMOD | 0.00019576567 |
| 3,534 | OPT: A New Framework for Overlapped and Parallel Triangulation in Large-scale Graphs | 2014 | SIGMOD | 6.9997025e-05 |
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