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Graph Sketches: Sparsification, Spanners, and Subgraphs

Summary: Presents graph sketches via linear projections: Õ(n ε^{-2}) random linear measurements suffice to build (1+ε)-approximate cut sparsifiers and O(ε^{-2}) measurements give additive estimates of small induced subgraph counts. Introduces adaptive-sketch spanner constructions for distances and shows these non/adaptive sketches yield single-pass dynamic-stream and low-round distributed/MapReduce algorithms. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1560
Venue
PODS
Year
2012
Pagerank
0.00015254436
Overall Rank
922 | 93.60%
DOI
-

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