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EFFICIENT COMPUTATION OF THE TUCKER DECOMPOSITION AND MOMENT TENSOR

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title
EFFICIENT COMPUTATION OF THE TUCKER DECOMPOSITION AND MOMENT TENSOR
author
Li, Zitong
abstract
Data can be organized in different ways. It is called a vector when organized as a 1D list, a matrix when organized as a 2D grid, and a tensor when organized as a grid of 3 or more dimensions. Tensor datasets are ubiquitous in scientific research. Examples include brain fMRI data, hyperspectral images, and results generated from physics simulations. Similar to matrix decompositions, tensor decompositions can be used to compress data and to find the data's underlying structure.
subject
High-Performance Computing
Randomized Algorithms
Statistical Moment Tensor
Tensor Decomposition
contributor
Ballard, Grey (committee chair)
Erway, Jennifer (committee member)
Pauca, Paul (committee member)
date
2022-05-24T08:36:10Z (accessioned)
2022-05-24T08:36:10Z (available)
2022 (issued)
degree
Computer Science (discipline)
identifier
http://hdl.handle.net/10339/100763 (uri)
language
en (iso)
publisher
Wake Forest University
type
Thesis

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