Unraveling Privacy Risks of Individual Fairness in Graph Neural Networks

30 January 2023

Papers citing "Unraveling Privacy Risks of Individual Fairness in Graph Neural Networks"

8 / 8 papers shown

Title
Unifying Unsupervised Graph-Level Anomaly Detection and Out-of-Distribution Detection: A Benchmark Yili Wang Yixin Liu Xu Shen Chenyu Li Kaize Ding Rui Miao Ying Wang Shirui Pan Xin Wang 24 6 0 21 Jun 2024
Large Language Models for Scientific Synthesis, Inference and Explanation Yizhen Zheng Huan Yee Koh Jiaxin Ju A. T. Nguyen Lauren T. May Geoffrey I. Webb Shirui Pan ELM 29 30 0 12 Oct 2023
CoactSeg: Learning from Heterogeneous Data for New Multiple Sclerosis Lesion Segmentation Yicheng Wu Zhonghua Wu Hengcan Shi Bjoern Picker W. Chong Jianfei Cai OOD 14 5 0 10 Jul 2023
Trustworthy Graph Neural Networks: Aspects, Methods and Trends He Zhang Bang Wu Xingliang Yuan Shirui Pan Hanghang Tong Jian Pei 34 98 0 16 May 2022
Achieving Fairness at No Utility Cost via Data Reweighing with Influence Peizhao Li Hongfu Liu TDI 25 45 0 01 Feb 2022
Differentially Private Temporal Difference Learning with Stochastic Nonconvex-Strongly-Concave Optimization Canzhe Zhao Yanjie Ze Jing Dong Baoxiang Wang Shuai Li 31 3 0 25 Jan 2022
Model Extraction Attacks on Graph Neural Networks: Taxonomy and Realization Bang Wu Xiangwen Yang Shirui Pan Xingliang Yuan MIACV MLAU 47 47 0 24 Oct 2020
Stealing Links from Graph Neural Networks Xinlei He Jinyuan Jia Michael Backes Neil Zhenqiang Gong Yang Zhang AAML 53 164 0 05 May 2020