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Softcover - 9783031315992
58,84 €
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Beschreibung
This book introduces the Learning-Augmented Network Optimization (LANO) paradigm, which interconnects network optimization with the emerging AI theory and algorithms and has been receiving a growing attention in network research. The authors present the topic based on a general stochastic network optimization model, and review several important theoretical tools that are widely adopted in network research, including convex optimization, the drift method, and mean-field analysis. The book then covers several popular learning-based methods, i.e., learning-augmented drift, multi-armed bandit and reinforcement learning, along with applications in networks where the techniques have been successfully applied. The authors also provide a discussion on potential future directions and challenges.
Details
| Verlag | Springer International Publishing |
| Ersterscheinung | 20. Juni 2023 |
| Maße | 24 cm x 16.8 cm |
| Gewicht | 333 Gramm |
| Format | Hardcover |
| ISBN-13 | 9783031315961 |
| Seiten | 71 |
Schlagwörter
Angewandte Informatik, Computer and Information Systems Applications, Computer Networks, Computer Science, Computernetzwerke und maschinelle Kommunikation, Informatik, Machine Learning, Maschinelles Lernen, Optimierung, Optimization, Stochastic Networks, Stochastik, Wahrscheinlichkeitsrechnung und Statistik
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