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Exploring Deep Learning Architectures for Graph Applications

Language EnglishEnglish
Book Paperback
Book Exploring Deep Learning Architectures for Graph Applications Irwin King
Libristo code: 36917993
Publishers LAP LAMBERT Academic Publishing, October 2020
Graph-structured data are the backbone of numerous real-world machine learning tasks, such as social... Full description
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113.57  лв
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Graph-structured data are the backbone of numerous real-world machine learning tasks, such as social networks, recommender systems, traffic networks, and so on. The fundamental challenge in solving these tasks is to find a way to encode graph structures as well as to incorporate various node or edge information so that machine learning models can easily exploit them. In this dissertation, we explore deep learning architectures, especially the graph neural networks for multiple graph learning applications, i.e., node classification, link prediction, spatiotemporal graph forecasting on irregular grid, and supervised sequence learning problems.

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About the book

Full name Exploring Deep Learning Architectures for Graph Applications
Author Irwin King
Language English
Binding Book - Paperback
Date of issue 2020
Number of pages 136
EAN 9786202917650
ISBN 6202917652
Libristo code 36917993
Publishers LAP LAMBERT Academic Publishing
Weight 221
Dimensions 150 x 220 x 8

Categories

Computing & Information Technology > Computer networking & communications
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