This book constitutes the thoroughly refereed proceedings of the First International Conference on Machine Learning for Networking, MLN 2018, held in Paris, France, in November 2018. The 22 revised full papers included in the volume were carefully reviewed and selected from 48 submissions. They present new trends in the following topics: Deep and reinforcement learning; Pattern recognition and classification for networks; Machine learning for network slicing optimization, 5G system, user behavior prediction, multimedia, IoT, security and protection; Optimization and new innovative machine learning methods; Performance analysis of machine learning algorithms; Experimental evaluations of machine learning; Data mining in heterogeneous networks; Distributed and decentralized machine learning algorithms; Intelligent cloud-support communications, resource allocation, energy-aware/green communications, software defined networks, cooperative networks, positioning and navigation systems, wireless communications, wireless sensor networks, underwater sensor networks.
| ISBN: | 9783030199449 |
| Publication date: | 10th May 2019 |
| Author: | Éric Renault |
| Publisher: | Springer Nature Switzerland AG |
| Format: | Paperback |
| Pagination: | 388 pages |
| Series: | Lecture Notes in Computer Science |
| Genres: |
Data mining Expert systems / knowledge-based systems Artificial intelligence Network hardware Applied computing |
This book constitutes the thoroughly refereed proceedings of the First International Conference on Machine Learning for Networking, MLN 2018, held in Paris, France, in November 2018. The 22 revised full papers included in the volume were carefully reviewed and selected from 48 submissions. They present new trends in the following topics: Deep and reinforcement learning; Pattern recognition and classification for networks; Machine learning for network slicing optimization, 5G system, user behavior prediction, multimedia, IoT, security and protection; Optimization and new innovative machine learning methods; Performance analysis of machine learning algorithms; Experimental evaluations of machine learning; Data mining in heterogeneous networks; Distributed and decentralized machine learning algorithms; Intelligent cloud-support communications, resource allocation, energy-aware/green communications, software defined networks, cooperative networks, positioning and navigation systems, wireless communications, wireless sensor networks, underwater sensor networks.
Machine Learning for Networking features in the following genres: Data mining, Expert systems / knowledge-based systems, Artificial intelligence, Network hardware, Applied computing
Machine Learning for Networking is available in Paperback
Machine Learning for Networking was written by Éric Renault and published by Springer Nature Switzerland AG
Machine Learning for Networking has 388 pages
Yes it is part of Lecture Notes in Computer Science series
£62.99