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We consider privacy in the context of streaming algorithms for cardinality estimation.
Access path selection in a relational database management system
P. Griffiths Selinger, M. M. Astrahan, D. D. Chamberlin, R. A. Lorie, and T. G. Price · 1979
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Probabilistic counting algorithms for data base applications
Philippe Flajolet and G Nigel Martin · 1985
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On adaptive sampling
Philippe Flajolet · 1990
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A linear-time probabilistic counting algorithm for database applications
Kyu-Young Whang, Brad T Vander-Zanden, and Howard M Taylor · 1990
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Counting distinct elements in a data stream
Ziv Bar-Yossef, TS Jayram, Ravi Kumar, D Sivakumar, and Luca Trevisan · 2002
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Bitmap algorithms for counting active flows on high speed links
Cristian Estan, George Varghese, and Mike Fisk · 2003
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Calibrating noise to sensitivity in private data analysis
Cynthia Dwork, Frank McSherry, Kobbi Nissim, and Adam Smith · 2006
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Summarizing data using bottom-k sketches
Edith Cohen and Haim Kaplan · 2007
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Hyperloglog: the analysis of a near-optimal cardinality estimation algorithm
Philippe Flajolet, Éric Fusy, Olivier Gandouet, and Frédéric Meunier · 2007
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Distinct-value synopses for multiset operations
Kevin Beyer, Rainer Gemulla, Peter J Haas, Berthold Reinwald, and Yannis Sismanis · 2009
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Order statistics and estimating cardinalities of massive data sets
Frédéric Giroire · 2009
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Pan-private algorithms via statistics on sketches
Darakhshan Mir, Shan Muthukrishnan, Aleksandar Nikolov, and Rebecca N Wright · 2011
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The johnson-lindenstrauss transform itself preserves differential privacy
Jeremiah Blocki, Avrim Blum, Anupam Datta, and Or Sheffet · 2012
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Hyperloglog in practice: Algorithmic engineering of a state of the art cardinality estimation algorithm
Stefan Heule, Marc Nunkesser, and Alexander Hall · 2013
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An algorithm for privacy-preserving distributed user statistics
Florian Tschorsch and Björn Scheuermann · 2013
Tail bounds for sums of geometric and exponential variables
Svante Janson · 2018
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Cardinality estimators do not preserve privacy
Damien Desfontaines, Andreas Lochbihler, and David Basin · 2019
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RRTxFM: Probabilistic counting for differentially private statistics
Saskia Nuñez von Voigt and Florian Tschorsch · 2019
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Differentially-private multi-party sketching for large-scale statistics
Seung Geol Choi, Dana Dachman-Soled, Mukul Kulkarni, and Arkady Yerukhimovich · 2020
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The Flajolet-Martin sketch itself preserves differential privacy: Private counting with minimal space
Adam Smith, Shuang Song, and Abhradeep Guha Thakurta · 2020
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https://datasketches.apache.org/ , 2021
Apache DataSketches · 2021
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Jalaj Upadhyay · 2014
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Back to the future: an even more nearly optimal cardinality estimation algorithm
Kevin J Lang · 2017
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Differentially private ordinary least squares
Or Sheffet · 2017
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Efficient differentially private F 0 F_{0} linear sketching
Rasmus Pagh and Nina Mesing Stausholm · 2021
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Information theoretic limits of cardinality estimation: Fisher meets shannon
Seth Pettie and Dingyu Wang · 2021
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Differentially private fractional frequency moments estimation with polylogarithmic space
Lun Wang, Iosif Pinelis, and Dawn Song · 2022
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