Improved Asymmetric Locality Sensitive Hashing (ALSH) for Maximum Inner Product Search (MIPS)

@inproceedings{Shrivastava2015ImprovedAL,
  title={Improved Asymmetric Locality Sensitive Hashing (ALSH) for Maximum Inner Product Search (MIPS)},
  author={Anshumali Shrivastava and Ping Li},
  booktitle={UAI},
  year={2015}
}
Recently we showed that the problem of Maximum Inner Product Search (MIPS) is efficient and it admits provably sub-linear hashing algorithms. In [23], we used asymmetric transformations to convert the problem of approximate MIPS into the problem of approximate near neighbor search which can be efficiently solved using L2-LSH. In this paper, we revisit the problem of MIPS and argue that the quantizations used in L2-LSH is suboptimal for MIPS compared to signed random projections (SRP) which is… CONTINUE READING
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Improved maximum inner product search with better theoretical guarantees

2017 International Joint Conference on Neural Networks (IJCNN) • 2017
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