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Tight Bounds for Lp Samplers, Finding Duplicates in Streams, and Related Problems

Summary: Near-optimal Lp-samplers: O(ε^{-p} log^2 n) space for p∈(1,2), O(ε^{-1} log^2 n) for p∈(0,1), and an O(log^2 n)-bit zero-error L0-sampler. Leads to O(log^2 n)-space duplicate detection and Ω(log^2 n) lower bounds via augmented-indexing, matching upper bounds for sampling, duplicates, and heavy hitters. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1534
Venue
PODS
Year
2011
Pagerank
0.00014129658
Overall Rank
1,094 | 92.40%
DOI
-

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

Rank Cited Paper Year Venue Pagerank
383 An Optimal Algorithm for the Distinct Elements Problem 2010 PODS 0.00024820873
1,629 Space-optimal Heavy Hitters with Strong Error Bounds 2009 PODS 0.00011085267
2,080 Optimal Sampling From Distributed Streams 2010 PODS 9.5899129e-05
2,282 Summarizing and Mining Inverse Distributions on Data Streams via Dynamic Inverse Sampling 2005 VLDB 9.1073603e-05
2,789 Optimal Sampling from Sliding Windows 2009 PODS 8.1249652e-05
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