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We describe a new cardinality estimation algorithm that is extremely space-efficient.
Modeling by shortest data description
J. Rissanen, J. (1978) · 1978
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Probabilistic counting algorithms for data base applications
P. Flajolet and G. Nigel Martin · 1985
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Arithmetic coding for data compression
I. Witten, R. Neal, J. Cleary · 1987
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A linear-time probabilistic counting algorithm for database applications
K. Whang, B. Vander-Zanden, and H. Taylor · 1990
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Counting distinct elements in a data stream
Z. Bar-Yossef, T. Jayram, R. Kumar, D. Sivakumar, and L. Trevisan · 2002
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Contemporary Combinatorics
Bela Bollobas · 2002
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PhD thesis, École Pol technique, France, 2004
M. Durand. Combinatoire analytique et algorithmique des ensembles de données · 2004
Cited alongside, same era.
Summarizing data using bottom-k sketches
E. Cohen and H. Kaplan · 2007
Cited alongside, same era.
Hyperloglog: the analysis of a near-optimal cardinality estimation algorithm
P. Flajolet, É. Fusy, O. Gandouet, and F. Meunier · 2008
Cited alongside, same era.
Distinct-value synopses for multiset operations
K. Beyer, R. Gemulla, P. J. Haas, B. Reinwald, and Y. Sismanis · 2009
Cited alongside, same era.
Order statistics and estimating cardinalities of massive data sets
F. Giroire · 2009
Cited alongside, same era.
New cardinality estimation algorithms for HyperLogLog sketches
O. Ertl
Cited in the paper.
An optimal algorithm for the distinct elements problem
D. M. Kane, J. Nelson, and D. P. Woodruff · 2010
Later among the works it cites.
Hyperloglog in practice: Algorithmic engineering of a state of the art cardinality estimation algorithm
S. Heule, M. Nunkesser, and A. Hall · 2013
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All-distances sketches, revisited: HIP estimators for massive graphs analysis
E. Cohen · 2014
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Streamed approximate counting of distinct elements: Beating optimal batch methods
D. Ting · 2014
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A Framework for Estimating Stream Expression Cardinalities
A. Dasgupta, K. Lang, L. Rhodes, and J. Thaler · 2016
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https://github.com/facebook/zstd
Cited in the paper.
https://datasketches.github.io/
Cited in the paper.
Cited in the paper.