Effect of Initial Configuration of Weights on Training and Function of Artificial Neural Networks

Effect of Initial Configuration of Weights on Training and Function of Artificial Neural Networks

The function and performance of neural networks are largely determined by the evolution of their weights and biases in the process of training, starting from the initial configuration of these parameters to one of the local minima of the loss function. We perform the quantitative statistical charact...

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Bibliographic Details
Main Authors: Ricardo J. Jesus, Mário L. Antunes, Rui A. da Costa, Sergey N. Dorogovtsev, José F. F. Mendes, Rui L. Aguiar
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Series:Mathematics
Subjects:
training
evolution of weights
deep learning
neural networks
artificial intelligence
Online Access:https://www.mdpi.com/2227-7390/9/18/2246

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