Theoretical Insights into Neural Networks and Deep Learning: Advancing Understanding, Interpretability, and Generalization
This work aims to provide profound insights into neural networks and deep learning, focusing on their functioning, interpretability, and generalization capabilities. It explores fundamental aspects such as network architectures, activation functions, and learning algorithms, analyzing their theoreti...
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| 主要な著者: | , |
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| フォーマット: | Conference or Workshop Item |
| 出版事項: |
Institute of Electrical and Electronics Engineers Inc.
2023
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| オンライン･アクセス: | http://scholars.utp.edu.my/id/eprint/37565/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173043343&doi=10.1109%2fWCONF58270.2023.10235042&partnerID=40&md5=bdac334c46f1fe39a9595ff410135bf2 |
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