| 書目名稱 | Diffusion Source Localization in Large Networks | | 編輯 | Lei Ying,Kai Zhu | | 視頻video | http://file.papertrans.cn/280/279019/279019.mp4 | | 叢書名稱 | Synthesis Lectures on Learning, Networks, and Algorithms | | 圖書封面 |  | | 描述 | Diffusion processes in large networks have been used to model many real-world phenomena, including how rumors spread on the Internet, epidemics among human beings, emotional contagion through social networks, and even gene regulatory processes. Fundamental estimation principles and efficient algorithms for locating diffusion sources can answer a wide range of important questions, such as identifying the source of a widely spread rumor on online social networks. This book provides an overview of recent progress on source localization in large networks, focusing on theoretical principles and fundamental limits. The book covers both discrete-time diffusion models and continuous-time diffusion models. For discrete-time diffusion models, the book focuses on the Jordan infection center; for continuous-time diffusion models, it focuses on the rumor center. Most theoretical results on source localization are based on these two types of estimators or their variants. This book also includes algorithms that leverage partial-time information for source localization and a brief discussion of interesting unresolved problems in this area. | | 出版日期 | Book 2018 | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-031-79285-4 | | isbn_softcover | 978-3-031-79284-7 | | isbn_ebook | 978-3-031-79285-4Series ISSN 2690-4306 Series E-ISSN 2690-4314 | | issn_series | 2690-4306 | | copyright | Springer Nature Switzerland AG 2018 |
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