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Stream quantiles via maximal entropy histograms
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posted on 2014-01-01, 00:00 authored by O Arandjelović, Duc-Son Pham, Svetha VenkateshSvetha VenkateshWe address the problem of estimating the running quantile of a data stream when the memory for storing observations is limited.We (i) highlight the limitations of approaches previously described in the literature which make them unsuitable for non-stationary streams, (ii) describe a novel principle for the utilization of the available storage space, and (iii) introduce two novel algorithms which exploit the proposed principle. Experiments on three large realworld data sets demonstrate that the proposed methods vastly outperform the existing alternatives.
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Title of book
Neural information processing : 21st International Conference ICONIP 2014 Kuching, Malaysia, November 3-6, 2014 Proceedings, Part IIVolume
8835Series
Lecture Notes in Computer ScienceChapter number
40Pagination
327 - 334Publisher
Springer VerlagPlace of publication
Berlin, GermanyISSN
0302-9743eISSN
1611-3349ISBN-13
9783319126395Language
engPublication classification
B1 Book chapter; B Book chapterCopyright notice
2014, Springer VerlagExtent
71Editor/Contributor(s)
Ck Loo, K Yap, K Wong, A Teoh, K HuangUsage metrics
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