IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Online ISSN : 1745-1337
Print ISSN : 0916-8508
Special Section on Information Theory and Its Applications
The Ratio of the Desired Parameters of Deep Neural Networks
Yasushi ESAKIYuta NAKAHARAToshiyasu MATSUSHIMA
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2022 Volume E105.A Issue 3 Pages 433-435

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Abstract

There have been some researchers that investigate the accuracy of the approximation to a function that shows a generating pattern of data by a deep neural network. However, they have confirmed only whether at least one function close to the function showing a generating pattern exists in function classes of deep neural networks whose parameter values are changing. Therefore, we propose a new criterion to infer the approximation accuracy. Our new criterion shows the existence ratio of functions close to the function showing a generating pattern in the function classes. Moreover, we show a deep neural network with a larger number of layers approximates the function showing a generating pattern more accurately than one with a smaller number of layers under the proposed criterion, with numerical simulations.

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© 2022 The Institute of Electronics, Information and Communication Engineers
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