Renault Йric, Boumerdassi Selma, Mьhlethaler Paul Machine Learning for Networking: Third International Conference, Mln 2020, Paris, France, November 24-26, 2020, Revised Selected Papers 9783030708658

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Автор: Renault Йric, Boumerdassi Selma, Mьhlethaler Paul
Название: Machine Learning for Networking: Third International Conference, Mln 2020, Paris, France, November 24-26, 2020, Revised Selected Papers
ISBN: 9783030708658
Издательство: Springer
Классификация:

Информационные технологии: общие вопросы

Сетевое оборудование

Извлечение знаний из данных

Анализ и синтез систем

Экспертные системы / системы баз знаний

Машинное обучение

ISBN-10: 3030708659
Обложка/Формат: Paperback
Страницы: 375
Вес: 0.55 кг.
Дата издания: 20.04.2021
Язык: English
Размер: 23.39 x 15.60 x 2.06 cm
Ссылка на Издательство: Link
Поставляется из: Германии
Описание: Better anomaly detection for access attacks using deep bidirectional LSTMs.- Using Machine Learning to Quantify the Robustness of Network Controllability.- Configuration faults detection in IP Virtual Private Networks based on machine learning.- Improving Android malware detection through dimensionality reduction techniques.- A Regret Minimization Approach to Frameless Irregular Repetition Slotted Aloha.- Mobility based Genetic algorithm for Heterogeneous wireless networks.- Geographical Information based Clustering Algorithm for Internet of Vehicles.- Active Probing for Improved Machine-Learned Recognition of Network Traffic.- A Dynamic Time Warping and Deep Neural Network Ensemble for Online Signature Verification.- Performance evaluation of some Machine Learning algorithms for Security Intrusion Detection.- Three Quantum Machine Learning Approaches for Mobile User Indoor-Outdoor Detection.- Learning resource allocation algorithms for cellular networks.- Enhanced Pub/Sub Communications for Massive IoT Traffic with SARSA Reinforcement Learning.- Deep Learning-Aided Spatial Multiplexing with Index Modulation.- A Self-Gated Activation Function SINSIG Based on the Sine Trigonometric for Neural Network Models.- Spectral Analysis for Automatic Speech Recognition and Enhancement.- Road sign Identification with Convolutional Neural Network using TensorFlow.- A Semi-Automated Approach for Identification of Trends in Android Ransomware Literature.- Towards Machine Learning in Distributed Array DBMS: Networking Considerations.- Deep Learning Environment Perception and Self-Tracking for Autonomous and Connected Vehicles.- Remote Sensing Scene Classification Based on Effective Feature Learning by Deep Residual Networks.- Identifying Device Types for Anomaly Detection in IoT.- A novel heuristic optimization algorithm for solving the Delay-Constrained Least-Cost problem.- Terms Extraction from Clustered Web Search Results.

Machine Learning for Networking: Third International Conference, Mln 2020, Paris, France, November 24-26, 2020, Revised Selected Papers, Renault Йric, Boumerdassi Selma, Mьhlethaler Paul