Preprints
Weilin Cong, Jian Kang, Hanghang Tong, Mehrdad Mahdavi
arXiv:2402.16387
IMBENS: Ensemble Class-imbalanced Learning in Python
Zhining Liu, Jian Kang, Hanghang Tong, Yi Chang
arXiv:2111.12776
Journal Papers
FairRankVis: A Visual Analytics Framework for Exploring Algorithmic Fairness in Graph Mining Models
Tiankai Xie, Yuxin Ma, Jian Kang, Hanghang Tong, Ross Maciejewski
TVCG 2021
Graph Ranking Auditing: Problem Definitions and Fast Solutions
Meijia Wang, Jian Kang, Nan Cao, Yinglong Xia, Wei Fan, Hanghang Tong
TKDE 2020
Conference Papers
Theoretical and Empirical Insights into the Origins of Degree Bias in Graph Neural Networks
Arjun Subramonian, Jian Kang, Yizhou Sun
NeurIPS 2024
PageRank Bandits for Link Prediction
Yikun Ban, Jiaru Zou, Zihao Li, Yunzhe Qi, Dongqi Fu, Jian Kang, Hanghang Tong, Jingrui He. PageRank Bandits for Link Prediction
NeurIPS 2024
On the Sensitivity of Individual Fairness: Measures and Robust Algorithms
Xinyu He, Jian Kang, Ruizhong Qiu, Fei Wang, Jose Sepulveda, Hanghang Tong
CIKM 2024
LARP: Language Audio Relational Pre-training for Cold-Start Playlist Continuation
Rebecca Salganik, Xiaohao Liu, Yunshan Ma, Jian Kang, Tat-Seng Chua
KDD 2024
Conformalized Link Prediction on Graph Neural Networks
Tianyi Zhao, Jian Kang, Lu Cheng
KDD 2024
Ensuring User-side Fairness in Dynamic Recommender Systems
Hyunsik Yoo, Zhichen Zeng, Jian Kang, Zhining Liu, David Zhou, Fei Wang, Eunice Chan, Hanghang Tong
WWW 2024
Deceptive Fairness Attacks on Graphs via Meta Learning
Jian Kang, Yinglong Xia, Ross Maciejewski, Jiebo Luo, Hanghang Tong
ICLR 2024
[Code]
BeMap: Balanced Message Passing for Fair Graph Neural Network
Xiao Lin, Jian Kang, Weilin Cong, Hanghang Tong
LoG 2023
[Code]
Do We Really Need Complicated Model Architectures For Temporal Networks?
Weilin Cong, Si Zhang, Jian Kang, Baichuan Yuan, Hao Wu, Xin Zhou, Hanghang Tong, Mehrdad Mahdavi
ICLR 2023 (Oral, 5%)
InfoFair: Information-Theoretic Intersectional Fairness
Jian Kang, Tiankai Xie, Xintao Wu, Ross Maciejewski, Hanghang Tong
IEEE Big Data 2022
iFiG: Individually Fair Multi-view Graph Clustering
Yian Wang, Jian Kang, Yinglong Xia, Jiebo Luo, Hanghang Tong
IEEE Big Data 2022
[Code]
JuryGCN: Quantifying Jackknife Uncertainty on Graph Convolutional Networks
Jian Kang*, Qinghai Zhou*, Hanghang Tong
KDD 2022
RawlsGCN: Towards Rawlsian Difference Principle on Graph Convolutional Network
Jian Kang, Yan Zhu, Yinglong Xia, Jiebo Luo, Hanghang Tong
WWW 2022
Individual Fairness for Graph Neural Networks: A Ranking based Approach
Yushun Dong, Jian Kang, Hanghang Tong, Jundong Li
KDD 2021
[Code]
InFoRM: Individual Fairness on Graph Mining
Jian Kang, Jingrui He, Ross Maciejewski, Hanghang Tong
KDD 2020
N2N: Network Derivative Mining
Jian Kang, Hanghang Tong
CIKM 2019
X-Rank: Explainable Ranking in Complex Multi-layered Networks
Jian Kang*, Scott Freitas*, Haichao Yu, Yinglong Xia, Nan Cao, Hanghang Tong
CIKM 2018
AURORA: Auditing PageRank on Large Graphs
Jian Kang, Meijia Wang, Nan Cao, Yinglong Xia, Wei Fan, Hanghang Tong
IEEE Big Data 2018
[Slides] [Code] (check out the updated results in our TKDE paper)
Visual Mining of Multi-sourced Networks
Haichao Yu, Jian Kang, Yinglong Xia, Nan Cao, Hanghang Tong
ChinaVis 2018