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Adaptive Harmony Learning and Optimization for Attributed Graph Clustering

  • Published:2022-07-18 Issue: Volume: Page:
  • ISSN:
  • Container-title:2022 International Joint Conference on Neural Networks (IJCNN)
  • language:
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Author:

Wu Daqing1,Guo Xiangyang1,Luo Xiao2,Qiao Ziyue3,Ma Jinwen1

Affiliation:

1. School of Mathematical Sciences, Peking University,Department of Information and Computing Sciences,Beijing,China

2. School of Mathematical Sciences, Peking University,Department of Probability and Statistics,Beijing,China

3. Computer Network Information Center, Chinese Academy of Sciences,Beijing,China

Funder

National Key Research and Development Program of China

Publisher

IEEE

Reference37 articles.

1. Comparing partitions

2. Normalized Mutual Information Feature Selection

3. Unsupervised deep embedding for clustering analysis;xie;ICML,2016

4. Visualizing data using t-sne;van der maaten;Journal of Machine Learning Research,2008

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Improved Attributed Graph Clustering with Representation and Structure Augmentation;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30

2. A Dual-channel Semi-supervised Learning Framework on Graphs via Knowledge Transfer and Meta-learning;ACM Transactions on the Web;2024-01-08

3. Hybrid Clustering Solutions Fusion based on Gated Three-way Decision;2023 International Joint Conference on Neural Networks (IJCNN);2023-06-18
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