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Continuous Distributed Counting for Non-monotonic Streams

Summary: Randomized algorithms for continual distributed counting on non‑monotonic streams with unknown drift μ, adversarial site assignment but random arrivals, achieving expected communication Õ(min{k/(|μ|ε), k n/ε, n}) with matching lower bounds. Extends to fractional Brownian inputs and yields F2 estimation and Bayesian linear regression applications. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1587
Venue
PODS
Year
2012
Pagerank
4.9507254e-05
Overall Rank
6,716 | 53.28%
DOI
-

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Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
11,823 Variability in Data Streams 2016 PODS 4.1945683e-05
11,853 Scalable Approximate Query Tracking over Highly Distributed Data Streams 2016 SIGMOD 4.1945683e-05
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