Titlebook: Machine Learning for Networking; Third International Éric Renault,Selma Boumerdassi,Paul Mühlethaler Conference proceedings 2021 Springer

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A Regret Minimization Approach to Frameless Irregular Repetition Slotted Aloha: IRSA-RM, purpose. We adopt one specific variant of reinforcement learning, Regret Minimization, to learn the protocol parameters. We explain why it is selected, how to apply it to our problem with centralized learning, and finally, we provide both simulation results and insights into the learning process. T

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Performance Evaluation of Some Machine Learning Algorithms for Security Intrusion Detection,to pin down when not handled, but most of the work done in this area remains difficult to compare, that‘s why the aim of our article is to analyze and compare intrusion detection techniques with several machine learning algorithms. Our research indicates which algorithm offers better overall perform

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0302-9743 ons, software de ned networks, cooperative networks, positioning and navigation systems, wireless communications, wireless sensor networks, underwater sensor networks.978-3-030-70865-8978-3-030-70866-5Series ISSN 0302-9743 Series E-ISSN 1611-3349

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Conference proceedings 2021uted and decentralized machine learning algorithms, intelligent cloud-support communications, ressource allocation, energy-aware communications, software de ned networks, cooperative networks, positioning and navigation systems, wireless communications, wireless sensor networks, underwater sensor networks.

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Using Machine Learning to Quantify the Robustness of Network Controllability,er link-based random and targeted attacks. We compare our approximations with existing analytical approximations and show that our machine learning based approximations significantly outperform the existing closed-form analytical approximations in case of both synthetic and real-world networks. Apar

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