A Kernel Propagation-Based Graph Convolutional Network Imbalanced Node Classification Model on Graph Data-Reference-Cited by-同舟云学术

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A Kernel Propagation-Based Graph Convolutional Network Imbalanced Node Classification Model on Graph Data

Published:2022-12-15 Issue: Volume: Page:
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Container-title:2022 IEEE International Conference on Networking, Sensing and Control (ICNSC)
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Author:

Bai Xiang-En¹,An Jing¹,Yu Zi-Bo²,Bao Han-Qiu³,Wang Ke-Fan⁴

Affiliation:

1. School of Computer Science and Information Engineering, Shanghai Institute of Technology,Shanghai,China

2. College of Applied Mathematics, Xi'an Jiaotong-Liverpool University,Suzhou,China

3. College of Electronic and Information Engineering, Tongji University,Shanghai,China

4. Shanghai Research Institute for Intelligent Autonomous Systems, Tongji University,Shanghai,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10004025/10004026/10004183.pdf?arnumber=10004183

Reference36 articles.

1. Inductive representation learning on large graphs;hamilton;Advances in neural information processing systems,2017

2. Classifying peer-to-peer applications using imbalanced concept-adapting very fast decision tree on IP data stream

3. A Unified Form of Fuzzy C-Means and K-Means algorithms and its Partitional Implementation

4. ICU Mortality Prediction: A Classification Algorithm for Imbalanced Datasets

5. Boosting-GNN: Boosting Algorithm for Graph Networks on Imbalanced Node Classification

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