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All-Distances Sketches, Revisited: HIP Estimators for Massive Graphs Analysis

Summary: Unified exposition of All-Distances Sketches (ADS) plus Historic Inverse Probability (HIP) estimators for scalable, near-linear per-node sketching of massive graphs. HIP halves variance of prior neighborhood-size estimates, yields polynomial gains for broader queries, is unbiased/simple, and empirically outperforms HyperLogLog. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1622
Venue
PODS
Year
2014
Pagerank
8.0918347e-05
Overall Rank
2,805 | 80.49%
DOI
10.1145/2594538.2594546

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