50 citations · 61 across the 6 of their papers we have counts for
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cs.LG2019
Accelerating Large-Scale Inference with Anisotropic Vector Quantization
Ruiqi Guo, Philip Sun, Erik Lindgren +4
Quantization based techniques are the current state-of-the-art for scaling maximum inner product search to massive databases. Traditional approaches to quantization aim to minimize…
cs.LG2019★ 2 cited
Local Orthogonal Decomposition for Maximum Inner Product Search
Xiang Wu, Ruiqi Guo, Sanjiv Kumar +1
Inverted file and asymmetric distance computation (IVFADC) have been successfully applied to approximate nearest neighbor search and subsequently maximum inner product search. In s…
cs.LG2019★ 6 cited
Efficient Inner Product Approximation in Hybrid Spaces
Xiang Wu, Ruiqi Guo, David Simcha +2
Many emerging use cases of data mining and machine learning operate on large datasets with data from heterogeneous sources, specifically with both sparse and dense components. For…