Yue Gao, Zizhao Zhang, Haojie Lin, Xibin Zhao, Shaoyi Du, Changqing Zou
Hypergraph learning is a technique for conducting learning on a hypergraph structure. In recent years, hypergraph learning has attracted increasing attention due to its flexibility and capability in modeling complex data correlation. In this paper, we first systematically review existing literature regarding hypergraph generation, including distance-based, representation-based, attribute-based, and network-based approaches. Then, we introduce the existing learning methods on a hypergraph, including transductive hypergraph learning, inductive hypergraph learning, hypergraph structure updating, and multi-modal hypergraph learning...
May 2022: IEEE Transactions on Pattern Analysis and Machine Intelligence