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BLISS: A Billion scale Index using Iterative Re-partitionin:
, In:
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
,
Gupta, Gaurav
;
Medini, Tharun
;
Shrivastava, Anshumali
. - p. 486-495 , 2022
Link:
https://dl.acm.org/doi/10.1145/3534678.3539414
RT T1 <cTitle>Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining</cTitle>: T1 <Title>BLISS: A Billion scale Index using Iterative Re-partitioning</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3539414&Exemplar=1&LAN=DE A1 Gupta, Gaurav A1 Medini, Tharun A1 Shrivastava, Anshumali A1 Smola, Alexander J. PB ACM YR 2022 K1 billion-scale K1 classification K1 learning-to-index K1 load-balance K1 search K1 Information systems K1 Information systems applications K1 Data mining K1 Nearest-neighbor search K1 Computing methodologies K1 Machine learning K1 Learning paradigms K1 Supervised learning K1 Supervised learning by classification K1 Information retrieval K1 Retrieval models and ranking K1 Top-k retrieval in databases SP 486 OP 495 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3534678.3539414 DO https://dl.acm.org/doi/10.1145/3534678.3539414 SF ELIB - SuUB Bremen
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