Tensor Robust Principal Component Analysis with A New Tensor Nuclear Norm.

Canyi Lu,Jiashi Feng,Yudong Chen,Wei Liu,Zhouchen Lin,Shuicheng Yan

IEEE Transactions on Pattern Analysis and Machine Intelligence（2020）

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摘要

In this paper, we consider the Tensor Robust Principal Component Analysis (TRPCA) problem, which aims to exactly recover the low-rank and sparse components from their sum. Our model is based on the recently proposed tensor-tensor product (or t-product) [14]. Induced by the t-product, we first rigorously deduce the tensor spectral norm, tensor nuclear norm, and tensor average rank, and show that th...

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关键词

Principal component analysis,Sparse matrices,Matrix decomposition,Numerical models,Noise measurement,Convex functions

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