Cantitate/Preț
Produs
Total produse
Vezi coșul
Machine Learning for Networking de Éric Renault

Machine Learning for Networking: Lecture Notes in Computer Science, cartea 13767

Editat de Éric Renault, Paul Mühlethaler
en Limba Engleză Paperback – 7 iul 2023
This book constitutes the post-conference proceedings of the 5th International Conference on Machine Learning for Networking, MLN 2022, held in Paris, France, November 28–30, 2022.
The 12 full papers presented in this book were carefully reviewed and selected from 27 submissions.
The papers present novel ideas, results, experiences and work-in-process on all aspects of Machine Learning and Networking.
Citește tot Restrânge

Din seria Lecture Notes in Computer Science

Preț: 34406 lei

Preț vechi: 43007 lei
-20%

Puncte Express: 516
Preț estimativ în valută:
6084€ • 6977$ • 5258£

Carte tipărită la comandă

Livrare economică 27 aprilie-11 mai

 Adaugă în coș

Wish list
Gift list
Am citit!
Adaugă în listă

Specificații

ISBN-13: 9783031361821
ISBN-10: 3031361822
Pagini: 192
Ilustrații: X, 180 p. 91 illus., 59 illus. in color.
Dimensiuni: 155 x 235 x 11 mm
Greutate: 0.3 kg
Ediția:1st edition 2023
Editura: Springer
Colecția Lecture Notes in Computer Science
Seria Lecture Notes in Computer Science

Locul publicării:Cham, Switzerland

Cuprins

Comparison of AI-based algorithms for low energy communication.- Development of an Intent-Based Network incorporating Machine Learning for service Assurance of E-commerce Online Stores.- Cyber-attack proactive defense using multivariate time series and machine learning with Fuzzy Inference-based Decision System.- iPerfOPS: a Tool for Machine Learning-Based Optimization through Protocol Selection.- GRAPHSEC -- Advancing the Application of AI/ML to Network Security through Graph Neural Networks.- Low Complexity Adaptive ML Approaches for End-to-End Latency Prediction.- TDMA-based MAC protocols designed or optimized using Artificial Intelligence for safety data dissemination in Vehicular ad-hoc network: A Survey.- A Machine Learning Based Approach to Detect Stealthy Cobalt Strike C\&C Activities from Encrypted Network Traffic.- Unified Emulation-Simulation Training Environment for Autonomous Cyber Agents.- Deep Learning Based Camera Switching for Sports Broadcasting.- Phisherman: Phishing Link Scanner.- Leader-Assisted Client Selection for Federated Learning in Iot via the Cooperation of Nearby Devices.