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20102025
most citedMinimizing Communication for Eigenproblems and the Singular Value Decomposition

19 citations · 28 across the 8 of their papers we have counts for

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5 papers · 1 filter

math.NA20211 cited

Randomized algorithms for rounding in the Tensor-Train format

Hussam Al Daas, Grey Ballard, Paul Cazeaux +5

The Tensor-Train (TT) format is a highly compact low-rank representation for high-dimensional tensors. TT is particularly useful when representing approximations to the solutions o…

math.NA2020

Parallel Algorithms for Tensor Train Arithmetic

Hussam Al Daas, Grey Ballard, Peter Benner

We present efficient and scalable parallel algorithms for performing mathematical operations for low-rank tensors represented in the tensor train (TT) format. We consider algorithm…

math.NA2019

A Generalized Randomized Rank-Revealing Factorization

Grey Ballard, James Demmel, Ioana Dumitriu +1

We introduce a Generalized Randomized QR-decomposition that may be applied to arbitrary products of matrices and their inverses, without needing to explicitly compute the products…

math.NA2019

PLANC: Parallel Low Rank Approximation with Non-negativity Constraints

Srinivas Eswar, Koby Hayashi, Grey Ballard +3

We consider the problem of low-rank approximation of massive dense non-negative tensor data, for example to discover latent patterns in video and imaging applications. As the size…

math.NA201019 cited

Minimizing Communication for Eigenproblems and the Singular Value Decomposition

Grey Ballard, James Demmel, Ioana Dumitriu

Algorithms have two costs: arithmetic and communication. The latter represents the cost of moving data, either between levels of a memory hierarchy, or between processors over a ne…