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Composite Quantization
2018
IEEE Transactions on Pattern Analysis and Machine Intelligence
This paper studies the compact coding approach to approximate nearest neighbor search. We introduce a composite quantization framework. It uses the composition of several (M ) elements, each of which is selected from a different dictionary, to accurately approximate a D-dimensional vector, thus yielding accurate search, and represents the data vector by a short code composed of the indices of the selected elements in the corresponding dictionaries. Our key contribution lies in introducing a
doi:10.1109/tpami.2018.2835468
pmid:29993737
fatcat:ncejlwqygbdo5hw5qtmacukh7u