Analyzing the Effect of Sampling in GNNs on Individual Fairness

8 September 2022

Papers citing "Analyzing the Effect of Sampling in GNNs on Individual Fairness"

24 / 24 papers shown

Title
Learning Fair Node Representations with Graph Counterfactual Fairness Jing Ma Ruocheng Guo Mengting Wan Longqi Yang Aidong Zhang Jundong Li FaML 66 79 0 10 Jan 2022
EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks Yushun Dong Ninghao Liu B. Jalaeian Jundong Li 62 120 0 11 Aug 2021
Personalized Counterfactual Fairness in Recommendation Yunqi Li Hanxiong Chen Shuyuan Xu Yingqiang Ge Yongfeng Zhang FaML OffRL 36 144 0 20 May 2021
User-oriented Fairness in Recommendation Yunqi Li H. Chen Zuohui Fu Yingqiang Ge Yongfeng Zhang FaML 117 233 0 21 Apr 2021
Sampling methods for efficient training of graph convolutional networks: A survey Xin Liu Yurui Lai Lei Deng Guoqi Li Xiaochun Ye Xiaochun Ye GNN 48 101 0 10 Mar 2021
On the Importance of Sampling in Training GCNs: Tighter Analysis and Variance Reduction Weilin Cong M. Ramezani M. Mahdavi 36 5 0 03 Mar 2021
Graph Neural Networks in Recommender Systems: A Survey Shiwen Wu Fei Sun Wentao Zhang Xu Xie Tengjiao Wang GNN 96 1,202 0 04 Nov 2020
Adversarial Learning for Debiasing Knowledge Graph Embeddings Mario Arduini Lorenzo Noci Federico Pirovano Ce Zhang Yash Raj Shrestha B. Paudel FaML 10 35 0 29 Jun 2020
A Survey on Knowledge Graph-Based Recommender Systems Qingyu Guo Fuzhen Zhuang Chuan Qin Hengshu Zhu Xing Xie Hui Xiong Qing He 104 735 0 28 Feb 2020
Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional Networks Difan Zou Ziniu Hu Yewen Wang Song Jiang Yizhou Sun Quanquan Gu GNN 59 282 0 17 Nov 2019
GraphSAINT: Graph Sampling Based Inductive Learning Method Hanqing Zeng Hongkuan Zhou Ajitesh Srivastava Rajgopal Kannan Viktor Prasanna GNN 98 962 0 10 Jul 2019
Operationalizing Individual Fairness with Pairwise Fair Representations Preethi Lahoti Krishna P. Gummadi Gerhard Weikum FaML 56 101 0 02 Jul 2019
Compositional Fairness Constraints for Graph Embeddings A. Bose William L. Hamilton FaML 42 258 0 25 May 2019
A Comprehensive Survey on Graph Neural Networks Zonghan Wu Shirui Pan Fengwen Chen Guodong Long Chengqi Zhang Philip S. Yu FaML GNN AI4TS AI4CE 249 8,441 0 03 Jan 2019
Adaptive Sampling Towards Fast Graph Representation Learning Wen-bing Huang Tong Zhang Yu Rong Junzhou Huang GNN 44 490 0 14 Sep 2018
Graph Convolutional Neural Networks for Web-Scale Recommender Systems Rex Ying Ruining He Kaifeng Chen Pong Eksombatchai William L. Hamilton J. Leskovec GNN BDL 159 3,513 0 06 Jun 2018
Deep Learning using Rectified Linear Units (ReLU) Abien Fred Agarap 47 3,195 0 22 Mar 2018
Sequence-Aware Recommender Systems Massimo Quadrana Paolo Cremonesi Dietmar Jannach 38 475 0 23 Feb 2018
Fair Clustering Through Fairlets Flavio Chierichetti Ravi Kumar Silvio Lattanzi Sergei Vassilvitskii FaML 35 430 0 15 Feb 2018
FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling Jie Chen Tengfei Ma Cao Xiao GNN 85 1,512 0 30 Jan 2018
Inductive Representation Learning on Large Graphs William L. Hamilton Z. Ying J. Leskovec 304 15,066 0 07 Jun 2017
Counterfactual Fairness Matt J. Kusner Joshua R. Loftus Chris Russell Ricardo M. A. Silva FaML 174 1,566 0 20 Mar 2017
Inherent Trade-Offs in the Fair Determination of Risk Scores Jon M. Kleinberg S. Mullainathan Manish Raghavan FaML 73 1,762 0 19 Sep 2016
Semi-Supervised Classification with Graph Convolutional Networks Thomas Kipf Max Welling GNN SSL 359 28,795 0 09 Sep 2016