Learning for Decision and Control in Stochastic Networks - Couverture rigide

Huang, Longbo

Couverture rigide

ISBN 10 : 3031315960 ISBN 13 : 9783031315961

Editeur : Springer International Publishing AG, 2023

Synopsis

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.

A propos du livre

À propos de l'auteur

Longbo Huang, Ph.D. is an Associate Professor at the Institute for Interdisciplinary Information Sciences (IIIS) at Tsinghua University, Beijing, China. He received his Ph.D. in EE from the University of Southern California, and then worked as a postdoctoral researcher in the EECS dept. at University of California at Berkeley before joining IIIS. Dr. Huang previously held visiting positions at the LIDS lab at MIT, the Chinese University of Hong Kong, Bell-labs France, and Microsoft Research Asia (MSRA). He was also a visiting scientist at the Simons Institute for the Theory of Computing at UC Berkeley in Fall 2016. Dr. Huang's research focuses on decision intelligence (AI for decisions), including deep reinforcement learning, online learning and reinforcement learning, learning-augmented network optimization, distributed optimization and machine learning.

Détails de l'édition

• Éditeur: Springer International Publishing AG
• Date d'édition: 2023
• Langue: anglais
• ISBN 10: 3031315960
• ISBN 13: 9783031315961
• Reliure: Relié
• Nombre de pages: 82
• Coordonnées du fabricant: ProductSafety@springernature.com; ProductSafety@springernature.com; ; Poststr. 9; Darmstadt; 64293; Allemagne