Hybrid tensor decomposition in neural network compression

DOI10.1016/j.neunet.2020.09.006zbMath1475.68325arXiv2006.15938OpenAlexW3037399553WikidataQ99724362 ScholiaQ99724362MaRDI QIDQ2057771

Bijiao Wu, Guangshe Zhao, Lei Deng, Dingheng Wang, Guoqi Li

Publication date: 7 December 2021

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2006.15938

zbMATH Keywords

balanced structurehierarchical Tuckertensor-trainhybrid tensor decompositionneural network compression

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Factorization of matrices (15A23) Multilinear algebra, tensor calculus (15A69)

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Uses Software

• htucker
• LOBPCG
• MNIST
• CIFAR
• ImageNet
• SqueezeDet
• AlexNet

Cites Work

• Tensor-Train Decomposition
• Optimization problems in contracted tensor networks
• A new scheme for the tensor representation
• An introduction to hierarchical (\(\mathcal H\)-) rank and TT-rank of tensors with examples
• Analysis of individual differences in multidimensional scaling via an \(n\)-way generalization of ``Eckart-Young decomposition
• Regularized Computation of Approximate Pseudoinverse of Large Matrices Using Low-Rank Tensor Train Decompositions
• Hierarchical Singular Value Decomposition of Tensors
• Algorithm 941
• Decompositions of a Higher-Order Tensor in Block Terms—Part II: Definitions and Uniqueness
• Preconditioned Low-Rank Methods for High-Dimensional Elliptic PDE Eigenvalue Problems

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