Power-law initialization algorithm for convolutional neural networks
Author:
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
https://link.springer.com/content/pdf/10.1007/s00521-023-08881-7.pdf
Reference24 articles.
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3. Go J, Baek B, Lee C (2004) Analyzing weight distribution of feedforward neural networks and efficient weight initialization. In: Joint IAPR international workshops on statistical techniques in pattern recognition (SPR) and structural and syntactic pattern recognition (SSPR). Springer, pp 840–849
4. Ruder S (2016) An overview of gradient descent optimization algorithms. arXiv:1609.04747
5. D. Nguyen and B. Widrow, Improving the learning speed of 2-layer neural networks by choosing initial values of the adaptive weights, in (1990) IJCNN international joint conference on neural networks. IEEE 1990:21–26
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