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標(biāo)題: Titlebook: Deep Neural Networks in a Mathematical Framework; Anthony L. Caterini,Dong Eui Chang Book 2018 The Author(s) 2018 deep learning.machine le [打印本頁]

作者: ETHOS    時間: 2025-3-21 20:09
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作者: Thyroxine    時間: 2025-3-21 20:56
Deutschland 20 Jahre nach dem Mauerfall require when performing gradient descent steps to optimize the neural network. To represent the dependence of a neural network on its parameters, we then introduce the notion of parameter-dependent maps, including distinct notation for derivatives with respect to parameters as opposed to state vari
作者: sed-rate    時間: 2025-3-22 00:45
Abschied vom Sozialstaat alter Pr?gungmeters, which allow us to perform gradient descent naturally over these vector spaces for each parameter. This approach contrasts with standard approaches to neural network modelling where the parameters are broken down into their components. We can avoid this unnecessary operation using the framewo
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作者: 古代    時間: 2025-3-22 18:47
Generic Representation of Neural Networks,meters, which allow us to perform gradient descent naturally over these vector spaces for each parameter. This approach contrasts with standard approaches to neural network modelling where the parameters are broken down into their components. We can avoid this unnecessary operation using the framewo
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SpringerBriefs in Computer Sciencehttp://image.papertrans.cn/d/image/264649.jpg
作者: 與野獸博斗者    時間: 2025-3-24 05:02
Deep Neural Networks in a Mathematical Framework978-3-319-75304-1Series ISSN 2191-5768 Series E-ISSN 2191-5776
作者: 較早    時間: 2025-3-24 09:24

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作者: nurture    時間: 2025-3-24 14:51
https://doi.org/10.1007/978-3-322-80729-8ss function derivatives directly over the inner product space in which the network parameters are defined. We dedicate this chapter to expressing three common neural network structures within this generic framework: the Multilayer Perceptron (MLP), the Convolutional Neural Network (CNN), and the Dee
作者: 發(fā)展    時間: 2025-3-24 20:06

作者: 比目魚    時間: 2025-3-25 01:36
https://doi.org/10.1007/978-3-8349-8569-9This chapter serves as a basic introduction to neural networks, including their history and some applications in which they have achieved state-of-the-art results.
作者: radiograph    時間: 2025-3-25 05:07
https://doi.org/10.1007/978-3-322-80729-8This chapter serves as a conclusion of this book and provides possible directions for future research.
作者: overbearing    時間: 2025-3-25 09:56
Introduction and Motivation,This chapter serves as a basic introduction to neural networks, including their history and some applications in which they have achieved state-of-the-art results.
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作者: 易于交談    時間: 2025-3-25 22:54
Generic Representation of Neural Networks,s for vector-valued functions and their derivatives. We use these tools in this chapter to describe the operations employed in a generic layered neural network. Since neural networks have been empirically shown to reap performance benefits from stacking increasingly more layers in succession, it is
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作者: Euphonious    時間: 2025-3-26 12:22
Book 2017at the disorder, though rare and highly morbid, is treatable when it is not misdiagnosed. Given the limited diagnostic and clinical training offered to clinicians, this book aims to equip professionals with the tools needed to improve the poor quality of life of youth with PNES..The text begins by i
作者: xanthelasma    時間: 2025-3-26 16:13
Changing Export Income and the Developing Countries’ Economy: A Diagrammatic Representationthe availability of labour force; (2) those whose traditional production is restricted because of the availability of suitable land; and (3) those whose production requires some imported inputs directly or indirectly, and thus have the extent of their output restricted by the availability of foreign exchange.
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作者: Estimable    時間: 2025-3-27 12:20
0067-0057 knowledge of various physical parameters. In addition, the density of very strong FeII lines becomes very large in the ultraviolet, and the lines can play a major role in the line blanketing. They need therefore to be taken into account in any energy balance argument.978-94-010-8285-3978-94-009-4023-9Series ISSN 0067-0057 Series E-ISSN 2214-7985
作者: 售穴    時間: 2025-3-27 15:07

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