MDP: Privacy-Preserving GNN Based on Matrix Decomposition and Differential Privacy-Reference-Cited by-同舟云学术

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MDP: Privacy-Preserving GNN Based on Matrix Decomposition and Differential Privacy

Published:2023-07 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Conference on Joint Cloud Computing (JCC)
language:
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Author:

Xu Wanghan¹,Shi Bin¹,Zhang Jiqiang¹,Feng Zhiyuan²,Pan Tianze³,Dong Bo⁴

Affiliation:

1. Xi’an Jiaotong University,School of Computer Science and Technology,Xi’an,China

2. Xi’an Jiaotong University,Qian Xuesen College,Xi’an,China

3. Xi’an Jiaotong University,School of Physics,Xi’an,China

4. Xi’an Jiaotong University,School of Distance Education,Xi’an,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10227855/10229517/10229600.pdf?arnumber=10229600

Reference32 articles.

1. Industrial Scale Privacy Preserving Deep Neural Network[J];zheng,2020

2. FlexGraph

3. Privacy-Preserving Graph Convolutional Networks for Text Classification[J];igamberdiev,2021

4. Survey and Open Problems in Privacy Preserving Knowledge Graph: Merging, Query, Representation, Completion and Applications[J];chen,2020

5. Graph neural network for traffic forecasting: A survey

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