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1. |
Record Nr. |
UNINA9911015684903321 |
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Autore |
Kang Yuhan |
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Titolo |
Mean Field Guided Machine Learning / / by Yuhan Kang, Hao Gao, Zhu Han |
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Pubbl/distr/stampa |
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Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
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ISBN |
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Edizione |
[1st ed. 2025.] |
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Descrizione fisica |
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1 online resource (248 pages) |
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Collana |
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Wireless Networks, , 2366-1445 |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Machine learning |
Telecommunication |
Artificial intelligence |
Machine Learning |
Communications Engineering, Networks |
Artificial Intelligence |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Preface -- Chapter 1 Overview of Mean Field Theory and Machine Learning -- Chapter 2 Mean Field Game and Machine Learning Basis -- Chapter 3 Opinion Evolution in Social Networks: Use Generative Adversarial Networks to Solve Mean Field Game -- Chapter 4 Data Augmentation using Mean Field Games -- Chapter 5 Mean Field Game Guided Deep Reinforcement Learning -- Chapter 6 Incentive Mechanism Design in Satellite-Based Federated Learning using Mean Field Evolutionary Approach -- Chapter 7 Client Selection in Hierarchical Federated Learning with Mean Field Game -- Chapter 8 Evolutionary Neural Architecture Search with Mean Field Game Selection Mechanism -- References -- Index. |
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Sommario/riassunto |
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This book explores the integration of Mean Field Game (MFG) theory with machine learning (ML), presenting both theoretical foundations and practical applications. Drawing from extensive research, it provides insights into how MFG can improve various ML techniques, including supervised learning, reinforcement learning, and federated learning. MFG theory and ML are converging to address critical challenges in |
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high-dimensional spaces and multi-agent systems. While ML has transformed industries by leveraging vast data and computational power, scalability and robustness remain key concerns. MFG theory, which models large populations of interacting agents, offers a mathematical framework to simplify and optimize complex systems, enhancing ML’s efficiency and applicability. By bridging these two fields, this book aims to drive innovation in scalable and robust machine learning. The integration of MFG with ML not only expands research possibilities but also paves the way for more adaptive and intelligent systems. Through this work, the authors hope to inspire further exploration and development in this promising interdisciplinary domain. With case studies and real-world examples, this book serves as a guide for researchers and students in communications and networks seeking to harness MFG’s potential in advancing ML. Industry managers, practitioners and government research workers in the fields of communications and networks will find this book a valuable resource as well. |
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2. |
Record Nr. |
UNINA9910483853403321 |
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Titolo |
Essentials of Rhinology / / edited by Hitesh Verma, Alok Thakar |
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Pubbl/distr/stampa |
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Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2021 |
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ISBN |
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Edizione |
[1st ed. 2021.] |
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Descrizione fisica |
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1 online resource (350 pages) |
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Collana |
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Disciplina |
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Soggetti |
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Otorhinolaryngology |
Therapeutics |
Diagnosis |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Endoscopic anatomy and surgery -- Rhinoplasty anatomy and procedures -- Nasal physiology and sinusitis -- Granulomatous disease and faciomaxillary trauma -- Diagnostic method and instrumentation in rhinology -- Tumours of nose and paranasal sinuses |
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-- Extended procedures -- Prevention and management of complications -- Septum, adenoid and epistaxis -- Radiotherapy, chemotherapy and quality of life. |
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Sommario/riassunto |
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This book serves as a practical guide for the otorhinolaryngologists to better understand the diseases of the sinonasal region, diagnosis, and management. The detailed knowledge of the complex anatomy of the sinonasal region is the key to surgical success. The text aims to help budding and practicing rhinologists to get an essence abreast of the current scientific advancement by engaging rhinologists with excellent awareness and knowledge as contributors. The book expands its span afar the usual by including topics on complications of endoscopic surgeries, empty sinus syndrome, packing material, open transcranial approach, biofilm, instruments, cavity management, and improved quality of life, etc. The purpose of microbiology, interventional radiology, pathology and nuclear medicine in the diagnosis and management of sinonasal diseases is contributed by authors from allied specialties. This book will be a useful resource for medical students, postgraduates in ENT, practicing rhinologists and general physicians in treating sinonasal diseases. . |
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