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Equivalence between nonnegative tensor factorization and tensorial probabilistic latent semantic analysis

机译:非负张量因子分解与张量概率潜在语义分析之间的等价关系

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This paper establishes a connection between NMF and PLSA on multi-way data, called NTF and T-PLSA respectively. Two types of T-PLSA models are proven to be equivalent to non-negative PARAFAC and non-negative Tucker3. This paper also shows that by running NTF and T-PLSA alternatively, they can jump out of each other's local minima and achieve a better clustering solution.
机译:本文建立了NMF和PLSA之间的多路数据连接,分别称为NTF和T-PLSA。两种类型的T-PLSA模型被证明等效于非负PARAFAC和非负Tucker3。本文还表明,通过交替运行NTF和T-PLSA,它们可以跳出彼此的本地最小值,从而获得更好的群集解决方案。

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