Neural networks and numerical analysis
著者
書誌事項
Neural networks and numerical analysis
（De Gruyter series in applied and numerical mathematics / Rémi Abgrall...[et al.], v. 6）
De Gruyter, 2022
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注記
Includes bibliographical references (p. [149]-153) and index
内容説明・目次
内容説明
This book uses numerical analysis as the main tool to investigate methods in machine learning and neural networks. The efficiency of neural network representations for general functions and for polynomial functions is studied in detail, together with an original description of the Latin hypercube method and of the ADAM algorithm for training. Furthermore, unique features include the use of Tensorflow for implementation session, and the description of on going research about the construction of new optimized numerical schemes.
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