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New LRTC Method Uses Novel Ky Fan p-k Norm Surrogate

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Researchers have introduced a new method for low-rank tensor completion (LRTC) that utilizes a novel nonconvex surrogate called the tensor nuclear norm to tensor Ky Fan p-k norm (TNPK). This approach aims to accurately approximate the tensor tubal rank and offers properties like scale invariance and parameter flexibility. The paper details a LRTC model and proves that low-rank tensors are local minimizers under specific conditions. An efficient algorithm, the alternating direction method of multipliers (ADMM), has been developed for this model, and experimental results show superior performance compared to existing methods. AI

RANK_REASON The cluster contains an academic paper detailing a new mathematical method and algorithm. [lever_c_demoted from research: ic=1 ai=0.4]

Read on arXiv cs.CV →

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New LRTC Method Uses Novel Ky Fan p-k Norm Surrogate

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The cluster contains an academic paper detailing a new mathematical method and algorithm. [lever_c_demoted from research: ic=1 ai=0.4]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Tingwen Huang ·

    Low-Rank Tensor Completion Based on Fractional Regularization with Ky Fan p-k Norm

    This paper addresses low-rank tensor completion (LRTC) by proposing a novel nonconvex surrogate, namely the ratio of the tensor nuclear norm to the tensor Ky Fan p-k norm (TNPK), to accurately approximate the tensor tubal rank. The TNPK possesses appealing properties, including s…

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