基于张量核范数的支持张量机
Support Tensor Machine Based on Nuclear Norm of Tensor
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摘要:通过引入张量的核范数,结合张量的展开矩阵等性质,提出了一种基于张量核范数的支持张量机( STM-NNT)并且构建了相应的算法来更有效地解决张量的分类问题. 该方法通过引入一个核范数正则项来控制权重矩阵的秩, 避免了过学习现象,达到了稀疏学习的目的.Abstract:A novel method, called support tensor machine based on nuclear norm of the tensor(STM-NNT) , is proposed
by the introduction of tensor nuclear norm, and corresponding algorithm is constructed for the efficient settlement of the classi- fying problem of tensor. The said method, by introducing a nuclear norm regular term thus to control the rank of weight ma- trix, saves us from over learning and thus to achieve the goal of sparse learning.