Hypergraph Learning for Multi-Modal Data 假设一个主体包含m个模态,可以把每个主体视作节点构建m个超图。为了达到全局的效果,需要为每个超图学习一个最优的权重系数来预测节点标签。
超图构造方法总结——Hypergraph Learning: Methods and Practices：一、超图生成方法 基于距离的方法 核心思想：使用特征空间中的距离来建模节点之间的关系。主要方式：最近邻居搜索：为每个节点找到最近的邻居构成超边。聚类：通过聚类算法将节点分到不同的簇中，每个簇构成一条超边。缺陷：受噪声和离群点...
超图构造方法总结--Hypergraph Learning: Methods and Practices超图学习是一种在超图结构上学习的方法。在本文中,我们首先系统重温了现有的超图生成方法,包括基于距离的,基于表示的,基于属性的和基于网络的方法
Hypergraph Learning: Methods and Practices (TPAMI, 2022) [paper] More Recent Advances in (Hyper)Graph Partitioning (ACM Computing Surveys, 2022) [paper] Survey of Hypergraph Neural Networks and Its Application to Action Recognition (CAAI International Conference on Artificial Intelligence, 2022) [paper...
Hypergraph learning: methods and practices. IEEE Trans. Pattern Anal. 44, 2548–2566 (2022). Google Scholar Collobert, R. et al. Natural language processing (almost) from scratch. J. Mach. Learn. Res. 12, 2493–2537 (2011). MATH Google Scholar Wolf, M. M., Klinvex, A. M. & ...
Du, C. Zou, Hypergraph learning: methods and practices. IEEE Trans. Pattern Analy. Mach. Intell. 44(5), 2548–2566 (2022) 2. Y. Gao, M. Wang, D. Tao, R. Ji, Q. Dai, 3-D object retrieval and recognition with hypergraph analysis. IEEE Trans. Image Process. 21, 4290–4303 (...
Hypergraph Learning: Methods and Practices (TPAMI, 2022) [paper] More Recent Advances in (Hyper)Graph Partitioning (ACM Computing Surveys, 2022) [paper] Survey of Hypergraph Neural Networks and Its Application to Action Recognition (CAAI International Conference on Artificial Intelligence, 2022) [paper...
Hypergraph Learning: Methods and Practices Hypergraph Nerual Networks HGNN+: General Hypergraph Nerual Networks Hypergraph Isomorphism Computation Contact Hyper-YOLO is maintained byiMoon-Lab, Tsinghua University. If you have any questions, please feel free to contact us via email:Yifan FengandJiangang ...
Hypergraph learning: methods and practices IEEE Trans. Pattern Anal. Mach. Intell., 44 (5) (2020), pp. 2548-2566 View in ScopusGoogle Scholar [41] Y. Yang, C. Huang, L. Xia, et al. Multi-behavior hypergraph-enhanced transformer for sequential recommendation Proc. 28th ACM SIGKDD Conf...
Generally speaking, most deep learning methods on hypergraph can be divided into spectral- based methods and spatial-based methods. As for the spectral-based methods, Feng et al. [53] proposed Hypergraph Neural Networks (HGNNs) to model non-pairwise relations based on the hypergraph Laplacian. ...