| |||||||
ShanghaiTech University Knowledge Management System
Improved Stability Bounds for Graph Convolutional Neural Networks Under Graph Perturbations | |
2024 | |
会议录名称 | 2024 IEEE INFORMATION THEORY WORKSHOP (ITW)
![]() |
ISSN | 2475-420X |
页码 | 307-312 |
发表状态 | 已发表 |
DOI | 10.1109/ITW61385.2024.10806975 |
摘要 | Graph convolutional neural networks (GCNNs) have emerged as powerful tools for processing signals or data supported by graphs. However, their effectiveness is compromised when perturbations exist in the graph structures. While previous research has studied the stability of GCNNs against such perturbations by analyzing the behavior of the graph convolutional filters, we found a significant discrepancy exists between the theoretical stability bounds and simulation outcomes. In this paper, we propose a novel approach to characterize the stability of GCNNs more accurately. Unlike existing methods that treat graph convolutional filters in each layer of a GCNN as separate SISO systems, our approach views them as a compact MIMO system. This perspective yields an improved stability characterization that aligns more closely with empirical observations and provides insights into designing GCNNs that are more resilient to graph perturbations. Numerical experiments on synthetic data confirm our theoretical findings and experiments on a movie recommendation problem demonstrate how it helps train stable GCNNs. |
会议地点 | Shenzhen, China |
会议日期 | 24-28 Nov. 2024 |
URL | 查看原文 |
语种 | 英语 |
来源库 | IEEE |
文献类型 | 会议论文 |
条目标识符 | https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/467849 |
专题 | 信息科学与技术学院 信息科学与技术学院_硕士生 信息科学与技术学院_PI研究组_赵子平组 |
作者单位 | School of Information Science and Technology, ShanghaiTech University, Shanghai, China |
第一作者单位 | 信息科学与技术学院 |
第一作者的第一单位 | 信息科学与技术学院 |
推荐引用方式 GB/T 7714 | Jun Zhang,Ziping Zhao. Improved Stability Bounds for Graph Convolutional Neural Networks Under Graph Perturbations[C],2024:307-312. |
条目包含的文件 | ||||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 |
个性服务 |
查看访问统计 |
谷歌学术 |
谷歌学术中相似的文章 |
[Jun Zhang]的文章 |
[Ziping Zhao]的文章 |
百度学术 |
百度学术中相似的文章 |
[Jun Zhang]的文章 |
[Ziping Zhao]的文章 |
必应学术 |
必应学术中相似的文章 |
[Jun Zhang]的文章 |
[Ziping Zhao]的文章 |
相关权益政策 |
暂无数据 |
收藏/分享 |
修改评论
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。