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This paper resolves one of the longest standing basic problems in the streaming computational model.
Selection and sorting with limited storage
J.I. Munro and M.S. Paterson · 1980
Earlier work this paper cites.
Random sampling techniques for space efficient online computation of order statistics of large datasets
Gurmeet Singh Manku, Sridhar Rajagopalan, and Bruce G. Lindsay · 1999
Earlier work this paper cites.
Space-efficient online computation of quantile summaries
Michael Greenwald and Sanjeev Khanna · 2001
Earlier work this paper cites.
Medians and beyond: New aggregation techniques for sensor networks
Nisheeth Shrivastava, Chiranjeeb Buragohain, Divyakant Agrawal, and Subhash Suri · 2004
Earlier work this paper cites.
A ( 1 / ε ) log ( 1 / ε ) (1/\varepsilon)\log(1/\varepsilon) space lower bound for finding ε \varepsilon -approximate quantiles in a data stream
Regant YS Hung and Hingfung F Ting · 2010
Cited alongside, same era.
Mergeable summaries
Pankaj K. Agarwal, Graham Cormode, Zengfeng Huang, Jeff Phillips, Zhewei Wei, and Ke Yi · 2012
Cited alongside, same era.
Quantiles over data streams: An experimental study
Lu Wang, Ge Luo, Ke Yi, and Graham Cormode · 2013
Cited alongside, same era.
Space-Efficient Data Structures, Streams, and Algorithms: Papers in Honor of J. Ian Munro, on the Occasion of His 66th Birthday
Andrej Brodnik, Alejandro Lopez-Ortiz, Venkatesh Raman, and Alfredo Viola · 2013
Later among the works it cites.
A randomized online quantile summary in O ( ( 1 / ε ) log ( 1 / ε ) ) {O}((1/\varepsilon)\log(1/\varepsilon)) words
David Felber and Rafail Ostrovsky · 2015
Later among the works it cites.
Quantiles and equidepth histograms over streams
Michael B. Greenwald and Sanjeev Khanna · 2016
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