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Decreasing Accelerated Gradient Descent Method for Nonnegative Matrix Factorization

机译:非负矩阵分解的递减加速梯度下降法

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In this paper, by bringing in a user defined nonnegative control matrix to form a new objective function, I modify the update rules correspondingly and propose a novel decreasing accelerated gradient descent method for nonnegative matrix factorization (DAGDM) which can make the matrix of the decomposition results achieve sparse. The control matrix also contains the weighting information, which puts different weight on different parts of the result matrix to be produced. This will provide a control interface of nonnegative matrix factorization to make a sparse and light basis matrix. Experimental results demonstrate the effectiveness of the proposed method.
机译:在本文中,通过引入用户定义的非负控制矩阵以形成新的目标函数,我相应地修改了更新规则,并提出了一种用于非负矩阵分解(DAGDM)的新颖的递减加速梯度下降方法,该方法可以使分解矩阵结果达到稀疏。控制矩阵还包含权重信息,该权重信息对要生成的结果矩阵的不同部分施加不同的权重。这将提供非负矩阵分解的控制界面,以创建稀疏和轻量级的矩阵。实验结果证明了该方法的有效性。

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