Fast and Accurate Tensor Completion with Total Variation Regularized Tensor Trains

We propose a new tensor completion method based on tensor trains. The to-be-completed tensor is modeled as a low-rank tensor train, where we use the known tensor entries and their coordinates to update the tensor train. A novel tensor train initialization procedure is proposed specifically for image...

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Bibliographic Details
Main Authors: Ko, Ching-Yun (Author), Batselier, Kim (Author), Yu, Wenjian (Author), Wong, Ngai (Author)
Other Authors: Massachusetts Institute of Technology. Research Laboratory of Electronics (Contributor), MIT-IBM Watson AI Lab (Contributor)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE), 2021-03-05T12:33:10Z.
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