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- W2008751576 abstract "We will also present simple information theoretic arguments to show that this is in essence the best we can do. The above approximation can be used for “similarity query” problems, widely used in Information Retrieval and other areas: after A has been preprocessed, we get “query” vectors x and must find the similarity of x to each row of A. Here, the similarity of two vectors is defined to be their dot product or their normalized dot product; our technique can handle both. Using an alternative method (essentially the technique of Achlioptas and McSherry in [1]), we also show another approximation A′′ which can be computed in" @default.
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- W2008751576 date "2003-01-12" @default.
- W2008751576 modified "2023-10-06" @default.
- W2008751576 title "Pass efficient algorithms for approximating large matrices" @default.
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- W2008751576 doi "https://doi.org/10.5555/644108.644147" @default.
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