Spectral tensor train parameterization of deep learning layers

We study low-rank parameterizations of weight matrices with embedded spectral properties in the Deep Learning context. The low-rank property leads to parameter efficiency and permits taking computational shortcuts when computing mappings. Spectral properties are often subject to constraints in optim...

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Bibliographic Details
Main Authors: OBUKHOV, A., RAKHUBA, M., LINIGER, A., HUANG, Zhiwu, GEORGOULIS, S., DAI, D., VAN Gool L.
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2021
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Online Access:https://ink.library.smu.edu.sg/sis_research/6259
https://ink.library.smu.edu.sg/context/sis_research/article/7262/viewcontent/Spectral_Tensor_Train_Parameterization_of_Deep_Learning_Layers.pdf
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Institution: Singapore Management University
Language: English
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