Federated graph neural network
Graph Neural Networks is a form of machine learning that has seen significant growth in popularity and use, owing to their natural affinity for capturing implicit representations that exist in real-world phenomena. Many of these real-world phenomena involve people-centric data, which are privacy-sen...
Saved in:
主要作者: | Koh, Tat You @ Arthur |
---|---|
其他作者: | Yu Han |
格式: | Final Year Project |
語言: | English |
出版: |
Nanyang Technological University
2021
|
主題: | |
在線閱讀: | https://hdl.handle.net/10356/153240 |
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 |
相似書籍
-
Federated learning for graph neural networks
由: Yan, Yige
出版: (2023) -
An investigation of the application of graph neural networks in recommendation systems
由: Koh, Jaylene Jia Ying
出版: (2023) -
Benchmarking novel graph neural networks
由: Bhagwat, Abhishek
出版: (2021) -
Graph convolutional neural networks for text categorization
由: Lakhotia, Suyash
出版: (2018) -
Implementation of high-performance graph neural network distributed learning framework
由: Lee, Cheng Han
出版: (2023)