Jian Kang

According to our database, Jian Kang authored at least 34 papers between 2018 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Non-exchangeable Conformal Prediction for Temporal Graph Neural Networks.

Tuo Wang, Jian Kang, Yujun Yan, Adithya Kulkarni, Dawei Zhou

CoRR, July, 2025

EVINET: Towards Open-World Graph Learning via Evidential Reasoning Network.

Weijie Guan, Haohui Wang, Jian Kang, Lihui Liu, Dawei Zhou

CoRR, June, 2025

CLIMB: Class-imbalanced Learning Benchmark on Tabular Data.

Zhining Liu, Zihao Li, Ze Yang, Tianxin Wei, Jian Kang, Yada Zhu, Hendrik F. Hamann, Jingrui He, Hanghang Tong

CoRR, May, 2025

Bridging Fairness and Uncertainty: Theoretical Insights and Practical Strategies for Equalized Coverage in GNNs.

Longfeng Wu, Yao Zhou, Jian Kang, Dawei Zhou

Proceedings of the ACM on Web Conference 2025, 2025

Characterizing Bias: Benchmarking Large Language Models in Simplified versus Traditional Chinese.

Hanjia Lyu, Jiebo Luo, Jian Kang, Allison Koenecke

Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency, 2025

2024

On the Generalization Capability of Temporal Graph Learning Algorithms: Theoretical Insights and a Simpler Method.

Weilin Cong, Jian Kang, Hanghang Tong, Mehrdad Mahdavi

CoRR, 2024

Ensuring User-side Fairness in Dynamic Recommender Systems.

Hyunsik Yoo, Zhichen Zeng, Jian Kang, Ruizhong Qiu, David Zhou, Zhining Liu, Fei Wang, Charlie Xu, Eunice Chan, Hanghang Tong

Proceedings of the ACM on Web Conference 2024, 2024

TrustLOG: The Second Workshop on Trustworthy Learning on Graphs.

Jingrui He, Jian Kang, Fatemeh Nargesian, Haohui Wang, An Zhang, Dawei Zhou

Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

Theoretical and Empirical Insights into the Origins of Degree Bias in Graph Neural Networks.

Arjun Subramonian, Jian Kang, Yizhou Sun

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

PageRank Bandits for Link Prediction.

Yikun Ban, Jiaru Zou, Zihao Li, Yunzhe Qi, Dongqi Fu, Jian Kang, Hanghang Tong, Jingrui He

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Conformalized Link Prediction on Graph Neural Networks.

Tianyi Zhao, Jian Kang, Lu Cheng

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

LARP: Language Audio Relational Pre-training for Cold-Start Playlist Continuation.

Rebecca Salganik, Xiaohao Liu, Yunshan Ma, Jian Kang, Tat-Seng Chua

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Deceptive Fairness Attacks on Graphs via Meta Learning.

Jian Kang, Yinglong Xia, Ross Maciejewski, Jiebo Luo, Hanghang Tong

Proceedings of the Twelfth International Conference on Learning Representations, 2024

On the Sensitivity of Individual Fairness: Measures and Robust Algorithms.

Xinyu He, Jian Kang, Ruizhong Qiu, Fei Wang, Jose Sepulveda, Hanghang Tong

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

Data Quality-aware Graph Machine Learning.

Yu Wang, Kaize Ding, Xiaorui Liu, Jian Kang, Ryan A. Rossi, Tyler Derr

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023

Ensuring User-side Fairness in Dynamic Recommender Systems.

Hyunsik Yoo, Zhichen Zeng, Jian Kang, Zhining Liu, David Zhou, Fei Wang, Eunice Chan, Hanghang Tong

CoRR, 2023

BeMap: Balanced Message Passing for Fair Graph Neural Network.

Xiao Lin, Jian Kang, Weilin Cong, Hanghang Tong

Proceedings of the Learning on Graphs Conference, 27-30 November 2023, Virtual Event., 2023

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

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

FairRankVis: A Visual Analytics Framework for Exploring Algorithmic Fairness in Graph Mining Models.

Tiankai Xie, Yuxin Ma, Jian Kang, Hanghang Tong, Ross Maciejewski

IEEE Trans. Vis. Comput. Graph., 2022

RawlsGCN: Towards Rawlsian Difference Principle on Graph Convolutional Network.

Jian Kang, Yan Zhu, Yinglong Xia, Jiebo Luo, Hanghang Tong

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

JuryGCN: Quantifying Jackknife Uncertainty on Graph Convolutional Networks.

Jian Kang, Qinghai Zhou, Hanghang Tong

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Algorithmic Fairness on Graphs: Methods and Trends.

Jian Kang, Hanghang Tong

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

TrustLOG: The First Workshop on Trustworthy Learning on Graphs.

Jian Kang, Shuaicheng Zhang, Bo Li, Jingrui He, Jian Pei, Dawei Zhou

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

iFiG: Individually Fair Multi-view Graph Clustering.

Yian Wang, Jian Kang, Yinglong Xia, Jiebo Luo, Hanghang Tong

Proceedings of the IEEE International Conference on Big Data, 2022

InfoFair: Information-Theoretic Intersectional Fairness.

Jian Kang, Tiankai Xie, Xintao Wu, Ross Maciejewski, Hanghang Tong

Proceedings of the IEEE International Conference on Big Data, 2022

2021

Graph Ranking Auditing: Problem Definition and Fast Solutions.

Meijia Wang, Jian Kang, Nan Cao, Yinglong Xia, Wei Fan, Hanghang Tong

IEEE Trans. Knowl. Data Eng., 2021

MultiFair: Multi-Group Fairness in Machine Learning.

Jian Kang, Tiankai Xie, Xintao Wu, Ross Maciejewski, Hanghang Tong

CoRR, 2021

Individual Fairness for Graph Neural Networks: A Ranking based Approach.

Yushun Dong, Jian Kang, Hanghang Tong, Jundong Li

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Fair Graph Mining.

Jian Kang, Hanghang Tong

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020

InFoRM: Individual Fairness on Graph Mining.

Jian Kang, Jingrui He, Ross Maciejewski, Hanghang Tong

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

2019

N2N: Network Derivative Mining.

Jian Kang, Hanghang Tong

Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

2018

AURORA: Auditing PageRank on Large Graphs.

Jian Kang, Hanghang Tong, Yinglong Xia, Wei Fan

CoRR, 2018

X-Rank: Explainable Ranking in Complex Multi-Layered Networks.

Jian Kang, Scott Freitas, Haichao Yu, Yinglong Xia, Nan Cao, Hanghang Tong

Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018

AURORA: Auditing PageRank on Large Graphs.

Jian Kang, Meijia Wang, Nan Cao, Yinglong Xia, Wei Fan, Hanghang Tong

Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018