Results 41 to 50 of about 2,491 (218)
Hypergraph-Supervised Deep Subspace Clustering
Mathematics, 2021 Auto-encoder (AE)-based deep subspace clustering (DSC) methods aim to partition high-dimensional data into underlying clusters, where each cluster corresponds to a subspace. As a standard module in current AE-based DSC, the self-reconstruction cost plays
Yu Hu, Hongmin Cai
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Error-Tolerant Non-Adaptive Learning of a Hidden Hypergraph [PDF]
, 2018 We consider the problem of learning the hypergraph using edge-detecting queries. In this model, the learner is allowed to query whether a set of vertices includes an edge from a hidden hypergraph. Except a few, all previous algorithms assume that a query'
Abasi, Hasan
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Datasets, tasks, and training methods for large-scale hypergraph learning
, 2023 Relations among multiple entities are prevalent in many fields, and hypergraphs are widely used to represent such group relations. Hence, machine learning on hypergraphs has received considerable attention, and especially much effort has been made in ...
Lee, Dongjin +5 more
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Hypergraph convolution and hypergraph attention
, 2020 Recently, graph neural networks have attracted great attention and achieved prominent performance in various research fields. Most of those algorithms have assumed pairwise relationships of objects of interest.
Zhang, F, Bai, Song, Torr, PHS
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Multiview Hypergraph Fusion Network for Change Detection in High-Resolution Remote Sensing Images
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingCurrently, convolutional neural networks and transformers have been the dominant paradigms for change detection (CD) thanks to their powerful local and global feature extraction capabilities. However, with the improvement of resolution, spatial, spectral,
Xue Zhao +5 more
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, 2021 The continuous emergence of drug-target interaction data provides an opportunity to construct a biological network for systematically discovering unknown interactions.
Yan, C +8 more
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Attribute-enhanced metric learning for face retrieval
EURASIP Journal on Image and Video Processing, 2018 Metric learning is a significant factor for media retrieval. In this paper, we propose an attribute label enhanced metric learning model to assist face image retrieval.
Yuchun Fang, Qiulong Yuan
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Hypergraph Learning with Hyperedge Expansion [PDF]
, 2012 We propose a new formulation called hyperedge expansion (HE) for hypergraph learning. The HE expansion transforms the hypergraph into a directed graph on the hyperedge level. Compared to the existing works (e.g. star expansion or normalized hypergraph cut), the learning results with HE expansion would be less sensitive to the vertex distribution among ...
Li Pu, Boi Faltings
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Hypergraph regularized sparse feature learning
, 2022 As 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.
X Guo (1378956) +3 more
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Noise-robust classification with hypergraph neural network
, 2021 This paper presents a novel version of the hypergraph neural network method. This method is utilized to solve the noisy label learning problem. First, we apply the PCA dimensional reduction technique to the feature matrices of the image datasets in order
Tran, Loc +3 more
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