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Sparse and Low-rank Tensor Estimation via Cubic Sketchings

In this paper, we propose a general framework for sparse and low-rank tensor estimation from cubic sketchings. A two-stage non-convex implementation is developed based on sparse tensor decomposition and thresholded gradient descent, which ensures exact recovery in the noiseless case and stable recov...

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Bibliografiske detaljer
Udgivet i:IEEE Trans Inf Theory
Main Authors: Hao, Botao, Zhang, Anru, Cheng, Guang
Format: Artigo
Sprog:Inglês
Udgivet: 2020
Fag:
Online adgang:https://ncbi.nlm.nih.gov/pmc/articles/PMC7978041/
https://ncbi.nlm.nih.gov/pubmed/33746244
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/tit.2020.2982499
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