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Hypergraph Learning: Methods and Practices
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021Hypergraph 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 ...
Yue Gao, Zizhao Zhang, Xibin Zhao
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On the effect of hyperedge weights on hypergraph learning [PDF]
Image and Vision Computing, 2017 Hypergraph is a powerful representation in several computer vision, machine learning and pattern recognition problems. In the last decade, many researchers have been keen to develop different hypergraph models. In contrast, no much attention has been paid to the design of hyperedge weights.
Sheng Huang, Ahmed Elgammal
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Clustering ensemble via structured hypergraph learning
Information Fusion, 2022Peng Zhou, Liang Du, Xuejun Li
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Cost-Sensitive Hypergraph Learning With F-Measure Optimization
IEEE Transactions on Cybernetics, 2023Nan Wang, Ruozhou Liang, Xibin Zhao
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Feature Learning Using Spatial-Spectral Hypergraph Discriminant Analysis for Hyperspectral Image
IEEE Transactions on Cybernetics, 2019Fulin Luo, Bo Du, Liangpei Zhang
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Combinative hypergraph learning for semi-supervised image classification
Neurocomputing, 2015Cheng Wang, Jonathan Li
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Adaptive Hypergraph Learning and its Application in Image Classification
IEEE Transactions on Image Processing, 2012Jun Yu, Dacheng Tao
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Joint hypergraph learning and sparse regression for feature selection
Pattern Recognition, 2017Zhihong Zhang, Lu Bai, Edwin R Hancock
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