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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 +5 more
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Hypergraph Structure Learning for Hypergraph Neural Networks
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022Hypergraphs are natural and expressive modeling tools to encode high-order relationships among entities. Several variations of Hypergraph Neural Networks (HGNNs) are proposed to learn the node representations and complex relationships in the hypergraphs. Most current approaches assume that the input hypergraph structure accurately depicts the relations
Derun Cai +5 more
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News recommendation via hypergraph learning
Proceedings of the sixth ACM international conference on Web search and data mining, 2013Personalized news recommender systems have gained increasing attention in recent years. Within a news reading community, the implicit correlations among news readers, news articles, topics and named entities, e.g., what types of named entities in articles are preferred by users, and why users like the articles, could be valuable for building an ...
Lei Li, Tao Li
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Adaptive algorithms for hypergraph learning
2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016Social media sharing platforms enable image content as well as context information (e.g., user friendships, geo-tags assigned to images) to be jointly analyzed in order to achieve accurate image annotation or successful image recommendation. The context information is expressed frequently in terms of high-order relations, such as the relations among ...
Aikaterini Chasapi +2 more
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Learning a hidden uniform hypergraph
Optimization Letters, 2017zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Huilan Chang +2 more
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Scalable Hypergraph Learning and Processing
2015 IEEE International Conference on Data Mining, 2015A hypergraph allows a hyperedge to connect more than two vertices, using which to capture the high-order relationships, many hypergraph learning algorithms are shown highly effective in various applications. When learning large hypergraphs, converting them to graphs to employ the distributed graph frameworks is a common approach, yet it results in ...
Jin Huang, Rui Zhang, Jeffrey Xu Yu
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Hypergraph regularized sparse feature learning
Neurocomputing, 2017As an important pre-processing stage in many machine learning and pattern recognition domains, feature selection deems to identify the most discriminate features for a compact data representation. As typical feature selection methods, Lasso and its variants using the l1-norm based regularization have received much attention in recent years.
Mingxia Liu +3 more
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Weight estimation in hypergraph learning
2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2015The unremitting rising popularity of social media has led to an exponential increase in web activity as manifested by the vast volume of uploaded images. This boundless volume of image data has triggered the interest in image tagging. Here, an efficient hypergraph weight estimation scheme is proposed that improves the accuracy of image tagging, using ...
Konstantinos Pliakos +1 more
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Hypergraph Attention Networks for Multimodal Learning
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020One of the fundamental problems that arise in multimodal learning tasks is the disparity of information levels between different modalities. To resolve this problem, we propose Hypergraph Attention Networks (HANs), which define a common semantic space among the modalities with symbolic graphs and extract a joint representation of the modalities based ...
Eun-Sol Kim +4 more
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Non-adaptive Learning of a Hidden Hypergraph
Theoretical Computer Science, 2015zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Abasi, Hasan +2 more
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