Singular Value Decomposition and Neural Networks

机译：奇异值分解与神经网络

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摘要

Singular Value Decomposition (SVD) constitutes a bridge between the linear algebra concepts and multi-layer neural networks-it is their linear analogy. Besides of this insight, it can be used as a good initial guess for the network parameters, leading to substantially better optimization results.

机译：奇异值分解（SVD）构成了线性代数概念和多层神经网络之间的桥梁-这是它们的线性类比。除了这种见识之外，它还可以用作对网络参数的良好初步猜测，从而获得更好的优化结果。

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《International Conference on Artificial Neural Networks》|2019年|153-164|共12页
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Bernhard Bermeitinger; Tomas Hrycej; Siegfried Handschuh;
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Singular Value Decomposition; Neural network; Deep neural network; Initialization; Optimization; Conjugate gradient;

机译：奇异值分解;神经网络;深度神经网络初始化;优化;共轭梯度;

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3. Applying Novel Time-Frequency Moments Singular Value Decomposition Method and Artificial Neural Networks for Ballistocardiography [J] . Alireza Akhbardeh, Sakari Junnila, Mikko Koivuluoma, EURASIP journal on advances in signal processing . 2006,第1期

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Singular Value Decomposition and Neural Networks

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