Please use this identifier to cite or link to this item:
https://elib.utmn.ru/jspui/handle/ru-tsu/39099| Title: | Analytic function approximation by path-norm-regularized deep neural networks |
| Authors: | Beknazaryan, A. Бекназарян, А. |
| Keywords: | analytic functions deep neural networks exponential convergence path norm regularization |
| Issue Date: | 2022 |
| Publisher: | MDPI |
| Citation: | Beknazaryan, A. (2022). Analytic function approximation by path-norm-regularized deep neural networks. Entropy (Basel, Switzerland), 24(8), 1136. doi:10.3390/e24081136 |
| Abstract: | We show that neural networks with an absolute value activation function and with network path norm, network sizes and network weights having logarithmic dependence on (Formula presented.) can (Formula presented.) -approximate functions that are analytic on certain regions of (Formula presented.). © 2022 by the author. |
| URI: | https://elib.utmn.ru/jspui/handle/ru-tsu/39099 |
| ISSN: | 1099-4300 |
| Appears in Collections: | Научные публикации, проиндексированные в SCOPUS и WoS |
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|---|---|---|---|---|
| 2-s2.0-85136547854.pdf | 299,65 kB | Adobe PDF | View/Open |
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