A Greedy Approach for Budgeted Maximum Inner Product Search

NeurIPS 2017 Hsiang-Fu YuCho-Jui HsiehQi LeiInderjit S. Dhillon

Maximum Inner Product Search (MIPS) is an important task in many machine learning applications such as the prediction phase of a low-rank matrix factorization model for a recommender system. There have been some works on how to perform MIPS in sub-linear time recently... (read more)

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