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Chaotic Feature Selection and Reconstruction in Time Series Prediction Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Yet Another Schatten Norm for Tensor Recovery

Authors : Chao Li, Lili Guo, Yu Tao, Jinyu Wang, Lin Qi, Zheng Dou

Published in: Neural Information Processing

Publisher: Springer International Publishing

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Abstract

In this paper, we introduce a new class of Schatten norms for tensor recovery. In the new norm, unfoldings of a tensor along not only every single order but also all combinations of orders are taken into account. Additionally, we prove that the proposed tensor norm has similar properties to matrix Schatten norm, and also provides several propositions which is useful in the recovery problem. Furthermore, for reliable recovery of a tensor with Gaussian measurements, we show the necessary size of measurements using the new norm. Compared to using conventional overlapped Schatten norm, the new norm results in less measurements for reliable recovery with high probability. Finally, experimental results demonstrate the efficiency of the new norm in video in-painting.

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previous chapter Neuron-Network Level Problem Decomposition Method for Cooperative Coevolution of Recurrent Networks for Time Series Prediction
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Metadata
Title
Yet Another Schatten Norm for Tensor Recovery
Authors
Chao Li
Lili Guo
Yu Tao
Jinyu Wang
Lin Qi
Zheng Dou
Copyright Year
2016
Book
Neural Information Processing

Print ISBN: 978-3-319-46674-3

Electronic ISBN: 978-3-319-46675-0

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-46675-0_6

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