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Higher-order Count Sketch: Dimensionality Reduction That Retains Efficient Tensor Operations
[article]
2019
arXiv
pre-print
Sketching is a randomized dimensionality-reduction method that aims to preserve relevant information in large-scale datasets. Count sketch is a simple popular sketch which uses a randomized hash function to achieve compression. In this paper, we propose a novel extension known as Higher-order Count Sketch (HCS). While count sketch uses a single hash function, HCS uses multiple (smaller) hash functions for sketching. HCS reshapes the input (vector) data into a higher-order tensor and employs a
arXiv:1901.11261v5
fatcat:75kha2ajufg3tjchuny7hzad7q