| 书目名称 | Hypergraph Computation | | 编辑 | Qionghai Dai,Yue Gao | | 视频video | | | 概述 | The first comprehensive and systematic overview for hypergraph computation.Rich blend of basic knowledge, theoretical analysis, algorithm introduction, and key applications.Describes hypergraph comput | | 丛书名称 | Artificial Intelligence: Foundations, Theory, and Algorithms | | 图书封面 |  | | 描述 | .This open access book discusses the theory and methods of hypergraph computation. ..Many underlying relationships among data can be represented using graphs, for example in the areas including computer vision, molecular chemistry, molecular biology, etc. In the last decade, methods like graph-based learning and neural network methods have been developed to process such data, they are particularly suitable for handling relational learning tasks. In many real-world problems, however, relationships among the objects of our interest are more complexthan pair-wise. Naively squeezing the complex relationships into pairwise ones will inevitably lead to loss of information which can be expected valuable for learning tasks. ..Hypergraph, as a generation of graph, has shown superior performance on modelling complex correlations compared with graph. Recent years have witnessed a great popularity of researches on hypergraph-related AI methods, which have been used in computer vision, social media analysis, .etc.. We summarize these attempts as a new computing paradigm, called hypergraph computation, which is to formulate thehigh-order correlations underneath the data using hypergraph, and the | | 出版日期 | Book‘‘‘‘‘‘‘‘ 2023 | | 关键词 | Hypergraph; Hypergraph Computation; Hypergraph Learning; Hypergraph Modelling; Hypergraph Neural Network | | 版次 | 1 | | doi | https://doi.org/10.1007/978-981-99-0185-2 | | isbn_softcover | 978-981-99-0187-6 | | isbn_ebook | 978-981-99-0185-2Series ISSN 2365-3051 Series E-ISSN 2365-306X | | issn_series | 2365-3051 | | copyright | The Editor(s) (if applicable) and The Author(s) 2023 |
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发表于 2025-3-21 17:18:16
