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We propose a quantization based approach for fast approximate Maximum Inner Product Search (MIPS).
Product code vector quantizers for waveform and voice coding
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Approximating matrix multiplication for pattern recognition tasks
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The netflix prize
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Improvement of the non-uniform version of berry-esseen inequality via paditz-siganov theorems
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The youtube video recommendation system
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Product quantization for nearest neighbor search
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Speeding up the xbox recommender system using a euclidean transformation for inner-product spaces
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A simpler and better lsh for maximum inner product search (mips)
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Asymmetric lsh (alsh) for sublinear time maximum inner product search (mips)
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An improved scheme for asymmetric LSH
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Going Deeper with Convolutions
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