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Machine Learning for Networking

Third International Conference, MLN 2020, Paris, France, November 24–26, 2020, Revised Selected Papers

  • Conference proceedings
  • © 2021

Overview

Editors:
  1. Éric Renault

    1. Laboratoire LIGM UMR 8049 CNRS, ESIEE Paris, Noisy-le-Grand, France

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  2. Selma Boumerdassi

    1. CNAM/CEDRIC, Paris, France

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    You can also search for this editor in PubMed   Google Scholar

  3. Paul Mühlethaler

    1. Inria/EVA Project, Paris, France

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    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 12629)

Part of the book sub series: Information Systems and Applications, incl. Internet/Web, and HCI (LNISA)

Included in the following conference series:

Conference proceedings info: MLN 2020.

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Table of contents (24 papers)

  1. Front Matter

    Pages i-xiii
    Download chapter PDF

  2. Better Anomaly Detection for Access Attacks Using Deep Bidirectional LSTMs

    • Henry Clausen, Gudmund Grov, Marc Sabate, David Aspinall
    Pages 1-18

  3. Using Machine Learning to Quantify the Robustness of Network Controllability

    • Ashish Dhiman, Peng Sun, Robert Kooij
    Pages 19-39

  4. Configuration Faults Detection in IP Virtual Private Networks Based on Machine Learning

    • El-Heithem Mohammedi, Emmanuel Lavinal, Guillaume Fleury
    Pages 40-56

  5. Improving Android Malware Detection Through Dimensionality Reduction Techniques

    • Vasileios Kouliaridis, Nektaria Potha, Georgios Kambourakis
    Pages 57-72

  6. A Regret Minimization Approach to Frameless Irregular Repetition Slotted Aloha: IRSA-RM

    • Iman Hmedoush, Cédric Adjih, Paul Mühlethaler
    Pages 73-92

  7. Mobility Based Genetic Algorithm for Heterogeneous Wireless Networks

    • Kamel Barka, Lyamine Guezouli, Samir Gourdache, Sara Ameghchouche
    Pages 93-106

  8. Geographical Information Based Clustering Algorithm for Internet of Vehicles

    • Rim Gasmi, Makhlouf Aliouat, Hamida Seba
    Pages 107-121

  9. Active Probing for Improved Machine-Learned Recognition of Network Traffic

    • Hamidreza Anvari, Paul Lu
    Pages 122-140

  10. A Dynamic Time Warping and Deep Neural Network Ensemble for Online Signature Verification

    • Mandlenkosi Victor Gwetu
    Pages 141-153

  11. Performance Evaluation of Some Machine Learning Algorithms for Security Intrusion Detection

    • Ouafae Elaeraj, Cherkaoui Leghris, Éric Renault
    Pages 154-166

  12. Three Quantum Machine Learning Approaches for Mobile User Indoor-Outdoor Detection

    • Frank Phillipson, Robert S. Wezeman, Irina Chiscop
    Pages 167-183

  13. Learning Resource Allocation Algorithms for Cellular Networks

    • Thi Thuy Nga Nguyen, Olivier Brun, Balakrishna J. Prabhu
    Pages 184-203

  14. Enhanced Pub/Sub Communications for Massive IoT Traffic with SARSA Reinforcement Learning

    • Carlos E. Arruda, Pedro F. Moraes, Nazim Agoulmine, Joberto S. B. Martins
    Pages 204-225

  15. Deep Learning-Aided Spatial Multiplexing with Index Modulation

    • Merve Turhan, Ersin Öztürk, Hakan Ali Çırpan
    Pages 226-236

  16. A Self-gated Activation Function SINSIG Based on the Sine Trigonometric for Neural Network Models

    • Khalid Douge, Aissam Berrahou, Youssef Talibi Alaoui, Mohammed Talibi Alaoui
    Pages 237-244

  17. Spectral Analysis for Automatic Speech Recognition and Enhancement

    • Jane Oruh, Serestina Viriri
    Pages 245-254

  18. Road Sign Identification with Convolutional Neural Network Using TensorFlow

    • Mohammed Kherarba, Mounir Tahar Abbes, Selma Boumerdassi, Mohammed Meddah, Abdelhak Benhamada, Mohammed Senouci
    Pages 255-264

  19. A Semi-automated Approach for Identification of Trends in Android Ransomware Literature

    • Tanya Gera, Jaiteg Singh, Deepak Thakur, Parvez Faruki
    Pages 265-283

  20. Towards Machine Learning in Distributed Array DBMS: Networking Considerations

    • Ramon Antonio Rodriges Zalipynis
    Pages 284-304
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  1. Machine Learning for Networking

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About this book

This book constitutes the thoroughly refereed proceedings of the Second International Conference on Machine Learning for Networking, MLN 2019, held in Paris, France, in December 2019. The 26 revised full papers included in the volume were carefully reviewed and selected from 75 submissions. They present and discuss new trends in 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, ressource allocation, energy-aware communications, software de ned networks, cooperative networks, positioning and navigation systems, wireless communications, wireless sensor networks, underwater sensor networks.

Editors and Affiliations

  • Laboratoire LIGM UMR 8049 CNRS, ESIEE Paris, Noisy-le-Grand, France

    Éric Renault

  • CNAM/CEDRIC, Paris, France

    Selma Boumerdassi

  • Inria/EVA Project, Paris, France

    Paul Mühlethaler

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