Results 11 to 20 of about 2,491 (218)
Hypergraph and Uncertain Hypergraph Representation Learning Theory and Methods
Mathematics, 2022 With the advent of big data and the information age, the data magnitude of various complex networks is growing rapidly. Many real-life situations cannot be portrayed by ordinary networks, while hypergraphs have the ability to describe and characterize ...
Liyan Zhang +5 more
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Semisupervised Hypergraph Discriminant Learning for Dimensionality Reduction of Hyperspectral Image [PDF]
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020 Semisupervised learning is an effective technique to represent the intrinsic features of a hyperspectral image (HSI), which can reduce the cost to obtain the labeled information of samples.
Fulin Luo +4 more
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Learning a Hidden Hypergraph [PDF]
, 2005 We consider the problem of learning a hypergraph using edge-detecting queries. In this model, the learner may query whether a set of vertices induces an edge of the hidden hypergraph or not.
Jiang Chen, Dana Angluin
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Adaptive dynamic hypergraph learning for ingredient aware food recommendation [PDF]
Scientific ReportsFood recommendation systems face fundamental challenges in modeling the complex, compositional relationships among users, foods, and ingredients. Traditional collaborative filtering and Graph Neural Networks rely on pairwise connections that oversimplify
Yazeed Alkhrijah +3 more
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Semi-Supervised Classification via Hypergraph Convolutional Extreme Learning Machine
Applied Sciences, 2021 Extreme Learning Machine (ELM) is characterized by simplicity, generalization ability, and computational efficiency. However, previous ELMs fail to consider the inherent high-order relationship among data points, resulting in being powerless on ...
Zhewei Liu +4 more
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Hypergraph-Mlp: learning on hypergraphs without message passing
ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)Hypergraphs are vital in modelling data with higher-order relations containing more than two entities, gaining prominence in machine learning and signal processing.
Chen, Siheng, Dong, Xiaowen, Tang, Bohan
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Self-Supervised Hypergraph Learning for Enhanced Multimodal Representation
IEEE AccessHypergraph neural networks have gained substantial popularity in capturing complex correlations between data items in multimodal datasets. In this study, we propose a novel approach called the self-supervised hypergraph learning (SHL) framework that ...
Hongji Shu +4 more
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EngineeringPractical real-world scenarios such as the Internet, social networks, and biological networks present the challenges of data scarcity and complex correlations, which limit the applications of artificial intelligence. The graph structure is a typical tool
Yue Gao +3 more
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Hypergraph Learning With Cost Interval Optimization
Proceedings of the AAAI Conference on Artificial Intelligence, 2018 In many classification tasks, the misclassification costs of different categories usually vary significantly. Under such circumstances, it is essential to identify the importance of different categories and thus assign different misclassification losses ...
Huang, Jin +5 more
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Hypergraph learning for identification of COVID-19 with CT imaging. [PDF]
Med Image Anal, 2021 Di D +15 more
europepmc +2 more sources