摘要: Inverted indexing is a popular non-exhaustive solution to large scale search. An inverted file built by quantizer such as k-means or tree structure. It has been found that multiple files, obtained independent random quantizers, are able achieve practically good recall and speed. Instead of computing the quantizers independently, we present method creates them jointly. Our jointly optimizes all code words in quantizers. Then it assigns these In experiments this shows significant improvement over various existing methods use On one-billion set SIFT vectors, our faster more accurate than recent state-of-the-art method.
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