Federated learning for graph neural networks

Federated learning for graph neural networks

This dissertation investigates the combination of graph neural networks (GNNs) and federated learning (FL) for addressing practical problems while preserving data privacy and reducing computational complexity. Specifically, we reproduce the Graph Clustered Federated Learning (GCFL) framework and...

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書目詳細資料
主要作者:	Yan, Yige
其他作者:	Tay Wee Peng
格式:	Thesis-Master by Coursework
語言:	English
出版:	Nanyang Technological University 2023
主題:	Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
在線閱讀:	https://hdl.handle.net/10356/167083
標簽:	添加標簽沒有標簽, 成為第一個標記此記錄!
機構:	Nanyang Technological University
語言:	English

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