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Hypergraph Neural Architecture Search
Proceedings of the AAAI Conference on Artificial IntelligenceIn recent years, Hypergraph Neural Networks (HGNNs) have achieved considerable success by manually designing architectures, which are capable of extracting effective patterns with high-order interactions from non-Euclidean data. However, such mechanism is extremely inefficient, demanding tremendous human efforts to tune diverse model parameters.
Wei Lin +3 more
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Disentangled Neural Architecture Search
2022 International Joint Conference on Neural Networks (IJCNN), 2022Xinyue Zheng +4 more
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Personalized Neural Architecture Search
2021 International Conference on Data Mining Workshops (ICDMW), 2021Cedric Kulbach, Steffen Thoma
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A Comprehensive Survey of Neural Architecture Search
ACM Computing Surveys, 2022Pengzhen Ren +2 more
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NPENAS: Neural Predictor Guided Evolution for Neural Architecture Search
IEEE Transactions on Neural Networks and Learning Systems, 2023Chen Wei, Chuang Niu, Haihong Hu
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BNAS: Efficient Neural Architecture Search Using Broad Scalable Architecture
IEEE Transactions on Neural Networks and Learning Systems, 2022Zixiang Ding +2 more
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A Survey on Evolutionary Neural Architecture Search
IEEE Transactions on Neural Networks and Learning Systems, 2023Yuqiao Liu, Yanan Sun, Bing Xue
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Evolutionary neural architecture search based on evaluation correction and functional units
Knowledge-Based Systems, 2022Ronghua Shang +2 more
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ModuleNet: Knowledge-Inherited Neural Architecture Search
IEEE Transactions on Cybernetics, 2022Yaran Chen, Ruiyuan Gao, Dongbin Zhao
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