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基于加权张量Schatten-p范数的鲁棒张量补全
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Abstract:
本文提出一种加权张量Schatten-p范数(0 < p < 1)正则化器用于鲁棒张量补全。建立了与增广拉格朗日乘子相关的相应算法。尽管所提加权张量Schatten-p拟范数是非凸的，但它不仅对奇异值的惩罚较小，而且能有效捕捉低秩特性。
In this paper, we present a weighted tensor Schatten-p norm (0 < p <1) regularizer for robust tensor completion. Corresponding algorithms associated with augmented Lagrangian multipliers are established. Although the proposed weighted tensor Schatten-p quasi-norm is non-convex, it appears not only to less penalize the singular values but also to be effective in capturing the low-rank property.
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