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International Conference on Machine Learning for Networking (2021 :)

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Machine learning for networking = 4th International Conference, MLN 2021, virtual event, December 1-3, 2021 : proceedings /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Machine learning for networking/ edited by Eric Renault, Selma Boumerdassi, Paul Muhlethaler.
Reminder of title:	4th International Conference, MLN 2021, virtual event, December 1-3, 2021 : proceedings /
remainder title:	MLN 2021
other author:	Renault, Eric.
corporate name:	International Conference on Machine Learning for Networking
Published:	Cham :Springer International Publishing : : 2022.,
Description:	x, 161 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	Evaluation of Machine Learning Methods for Image Classification: A Case Study of Facility Surface Damage -- One-Dimensional Convolutional Neural Network for Detection and Mitigation of DDoS Attacks in SDN -- Multi-Armed Bandit-based Channel Hopping: Implementation on Embedded Devices -- Cross Inference of Throughput Profiles Using Micro Kernel Network Method -- Machine Learning Models for Malicious Traffic Detection in IoT networks /IoT-23 dataset -- Application and Mitigation of the Evasion Attack against a Deep Learning Based IDS for Io -- DynamicDeepFlow: An Approach for Identifying Changes in Network Traffic Flow Using Unsupervised Clustering -- Unsupervised Anomaly Detection using a new Knowledge Graph Model for Network Activity and Events -- Deep Reinforcement Learning for Cost-Effective Controller Placement in Software-Defined Multihop Wireless Networking -- Distance estimation using LORA and neural networks.
Contained By:	Springer Nature eBook
Subject:	Machine learning - Congresses. -
Online resource:	https://doi.org/10.1007/978-3-030-98978-1
ISBN:	9783030989781

Machine learning for networking = 4th International Conference, MLN 2021, virtual event, December 1-3, 2021 : proceedings /
Machine learning for networking4th International Conference, MLN 2021, virtual event, December 1-3, 2021 : proceedings /[electronic resource] :MLN 2021edited by Eric Renault, Selma Boumerdassi, Paul Muhlethaler. - Cham :Springer International Publishing :2022. - x, 161 p. :ill. (some col.), digital ;24 cm. - Lecture notes in computer science,131750302-9743 ;. - Lecture notes in computer science ;13175..

Evaluation of Machine Learning Methods for Image Classification: A Case Study of Facility Surface Damage -- One-Dimensional Convolutional Neural Network for Detection and Mitigation of DDoS Attacks in SDN -- Multi-Armed Bandit-based Channel Hopping: Implementation on Embedded Devices -- Cross Inference of Throughput Profiles Using Micro Kernel Network Method -- Machine Learning Models for Malicious Traffic Detection in IoT networks /IoT-23 dataset -- Application and Mitigation of the Evasion Attack against a Deep Learning Based IDS for Io -- DynamicDeepFlow: An Approach for Identifying Changes in Network Traffic Flow Using Unsupervised Clustering -- Unsupervised Anomaly Detection using a new Knowledge Graph Model for Network Activity and Events -- Deep Reinforcement Learning for Cost-Effective Controller Placement in Software-Defined Multihop Wireless Networking -- Distance estimation using LORA and neural networks.

This book constitutes the thoroughly refereed proceedings of the 4th International Conference on Machine Learning for Networking, MLN 2021, held in Paris, France, in December 2021. The 10 revised full papers included in the volume were carefully reviewed and selected from 30 submissions. They present and discuss new trends in in deep and reinforcement learning, pattern recognition and classification for networks, machine learning for network slicing optimization, 5G systems, 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 communications, software-defined networks, cooperative networks, positioning and navigation systems, wireless communications, wireless sensor networks, and underwater sensor networks.

ISBN: 9783030989781

Standard No.: 10.1007/978-3-030-98978-1doiSubjects--Topical Terms:

576368
Machine learning
--Congresses.

LC Class. No.: Q325.5 / .I58 2021

Dewey Class. No.: 004.6

Machine learning for networking = 4th International Conference, MLN 2021, virtual event, December 1-3, 2021 : proceedings /
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