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Deplump for streaming data

Abstract:
We present a general-purpose, loss less compressor for streaming data. This compressor is based on the deplump probabilistic compressor for batch data. Approximations to the inference procedure used in the probabilistic model underpinning deplump are introduced that yield the computational asyptotics necessary for stream compression. We demonstrate the performance of this streaming deplump variant relative to the batch compressor on a benchmark corpus and find that it performs equivalently well despite these approximations. We also explore the performance of the streaming variant on corpora that are too large to be compressed by batch deplump and demonstrate excellent compression performance.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/DCC.2011.43

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author


Publisher:
IEEE
Host title:
Data Compression Conference
Journal:
Data Compression Conference More from this journal
Pages:
363-372
Publication date:
2011-04-11
DOI:
ISSN:
1068-0314
ISBN:
9781612842790


Keywords:
Pubs id:
pubs:417981
UUID:
uuid:0815eb9e-1237-42fa-a4ec-1345fbd419fd
Local pid:
pubs:417981
Source identifiers:
417981
Deposit date:
2017-03-23

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