1.1k citations · 3.9k across the 74 of their papers we have counts for
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math.NA2019★ 10 cited
Low-Rank Tucker Approximation of a Tensor From Streaming Data
Yiming Sun, Yang Guo, Charlene Luo +2
This paper describes a new algorithm for computing a low-Tucker-rank approximation of a tensor. The method applies a randomized linear map to the tensor to obtain a sketch that cap…
math.NA2019★ 2 cited
Streaming Low-Rank Matrix Approximation with an Application to Scientific Simulation
Joel A. Tropp, Alp Yurtsever, Madeleine Udell +1
This paper argues that randomized linear sketching is a natural tool for on-the-fly compression of data matrices that arise from large-scale scientific simulations and data collect…