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Tensor decompositions and algorithms, with applications to tensor learning
[article]
2021
arXiv
pre-print
A new algorithm of the canonical polyadic decomposition (CPD) presented here. It features lower computational complexity and memory usage than the available state of the art implementations. We begin with some examples of CPD applications to real world problems. A short summary of the main contributions in this work follows. In chapter 1 we review classical tensor algebra and geometry, with focus on the CPD. Chapter 2 focuses on tensor compression, which is considered (in this work) to be one
arXiv:2110.05997v1
fatcat:jktyucn73rgurg52kh4itgynmi