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Multiplicative update for a class of constrained optimization problems related to NMF and its global convergence

机译:与NMF及其全球收敛相关的一类受约束优化问题的乘法更新

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Multiplicative updates are widely used for nonnegative matrix factorization (NMF) as an efficient computational method. In this paper, we consider a class of constrained optimization problems in which a polynomial function of the product of two matrices is minimized subject to the nonnegativity constraints. These problems are closely related to NMF because the polynomial function covers many error function used for NMF. We first derive a multiplicative update rule for those problems by using the unified method developed by Yang and Oja. We next prove that a modified version of the update rule has the global convergence property in the sense of Zangwill under certain conditions. This result can be applied to many existing multiplicative update rules for NMF to guarantee their global convergence.
机译:乘法更新广泛用于非负矩阵分解(NMF)作为有效的计算方法。在本文中,我们考虑一类受约束的优化问题,其中两个矩阵的乘积的多项式函数被最小化对非承诺约束。这些问题与NMF密切相关,因为多项式函数涵盖用于NMF的许多误差函数。我们首先使用yang和oja开发的统一方法来派生这些问题的乘法更新规则。接下来,我们证明了更新规则的修改版本在某些条件下具有Zangigl意义上的全球融合属性。此结果可应用于NMF的许多现有乘法更新规则,以保证其全球收敛。

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