HOGMMNC: a higher order graph matching with multiple network constraints model for gene‐drug regulatory modules identification
Sign Up to like & getrecommendations! Published in 2019 at "Bioinformatics"
DOI: 10.1093/bioinformatics/bty662
Abstract: Motivation: The emergence of large amounts of genomic, chemical, and pharmacological data provides new opportunities and challenges. Identifying gene‐drug associations is not only crucial in providing a comprehensive understanding of the molecular mechanisms of drug… read more here.
Keywords: higher order; gene drug; drug; order graph ... See more keywords
Local Expansion and Optimization for Higher-Order Graph Clustering
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2019.2923228
Abstract: Graph clustering aims to identify clusters that feature tighter connections between internal nodes than external nodes. We noted that conventional clustering approaches based on a single vertex or edge cannot meet the requirements of clustering… read more here.
Keywords: order graph; expansion optimization; order; local expansion ... See more keywords
Tensorial Multi-View Clustering via Low-Rank Constrained High-Order Graph Learning
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Circuits and Systems for Video Technology"
DOI: 10.1109/tcsvt.2022.3143848
Abstract: Multi-view clustering aims to partition multi-view data into different categories by optimally exploring the consistency and complementary information from multiple sources. However, most existing multi-view clustering algorithms heavily rely on the similarity graphs from respective… read more here.
Keywords: view; high order; multi view; view clustering ... See more keywords
Hyperspectral Unmixing Using Higher-Order Graph Regularized NMF With Adaptive Feature Selection
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2023.3275740
Abstract: Recently, graph learning methods have attracted much research attention, which uses first-order nearest-neighbor relation between pixels to construct adjacency graphs for capturing smooth abundance. However, the first-order nearest-neighbor information neglects the shared domain structure of… read more here.
Keywords: higher order; feature; order graph; order ... See more keywords
Hybrid Low-Order and Higher-Order Graph Convolutional Networks
Sign Up to like & getrecommendations! Published in 2020 at "Computational Intelligence and Neuroscience"
DOI: 10.1155/2020/3283890
Abstract: With the higher-order neighborhood information of a graph network, the accuracy of graph representation learning classification can be significantly improved. However, the current higher-order graph convolutional networks have a large number of parameters and high… read more here.
Keywords: order; network; graph convolutional; convolutional networks ... See more keywords