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A Feature-Driven Fixed-Ratio Lossy Compression Framework fo..:
, In:
2023 IEEE 39th International Conference on Data Engineering (ICDE)
,
Rahman, Md Hasanur
;
Di, Sheng
;
Zhao, Kai
... - p. 1461-1474 , 2023
Link:
https://doi.org/10.1109/ICDE55515.2023.00116
RT T1 <cTitle>2023 IEEE 39th International Conference on Data Engineering (ICDE)</cTitle>: T1 <Title>A Feature-Driven Fixed-Ratio Lossy Compression Framework for Real-World Scientific Datasets</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10184704&Exemplar=1&LAN=DE A1 Rahman, Md Hasanur A1 Di, Sheng A1 Zhao, Kai A1 Underwood, Robert A1 Li, Guanpeng A1 Cappello, Franck YR 2023 SN 2375-026X K1 Correlation K1 Instruments K1 Computational modeling K1 Memory K1 Performance gain K1 Data engineering K1 Compressors K1 Lossy Compression K1 Scientific Data Management K1 Machine Learning K1 Data Features SP 1461 OP 1474 LK http://dx.doi.org/https://doi.org/10.1109/ICDE55515.2023.00116 DO https://doi.org/10.1109/ICDE55515.2023.00116 SF ELIB - SuUB Bremen
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