Jian Kang

48 papers A* 13A 6B 2Journal 21Unranked 6
YearRankTypeTitle / Venue / Authors
2026 J jnl
MusicSem: A Semantically Rich Language-Audio Dataset of Natural Music Descriptions.
CoRR
Rebecca Salganik, Teng Tu, Fei-Yueh Chen, Xiaohao Liu, Keifeng Lu, Ethan Luvisia, Zhiyao Duan, Guillaume Salha-Galvan, Anson Kahng, Yunshan Ma, Jian Kang
2025 A* conf
Bridging Fairness and Uncertainty: Theoretical Insights and Practical Strategies for Equalized Coverage in GNNs.
WWW
Longfeng Wu, Yao Zhou, Jian Kang, Dawei Zhou
2025 J jnl
CLIMB: Class-imbalanced Learning Benchmark on Tabular Data.
CoRR
Zhining Liu, Zihao Li, Ze Yang, Tianxin Wei, Jian Kang, Yada Zhu, Hendrik F. Hamann, Jingrui He, Hanghang Tong
2025 — conf
Characterizing Bias: Benchmarking Large Language Models in Simplified versus Traditional Chinese.
FAccT
Hanjia Lyu, Jiebo Luo, Jian Kang, Allison Koenecke
2025 J jnl
Characterizing Bias: Benchmarking Large Language Models in Simplified versus Traditional Chinese.
CoRR
Hanjia Lyu, Jiebo Luo, Jian Kang, Allison Koenecke
2025 — conf
EVI
KDD (2)
Weijie Guan, Haohui Wang, Jian Kang, Lihui Liu, Dawei Zhou
2025 J jnl
EVINET: Towards Open-World Graph Learning via Evidential Reasoning Network.
CoRR
Weijie Guan, Haohui Wang, Jian Kang, Lihui Liu, Dawei Zhou
2025 J jnl
FairExpand: Individual Fairness on Graphs with Partial Similarity Information.
CoRR
Rebecca Salganik, Yibin Wang, Guillaume Salha-Galvan, Jian Kang
2025 — conf
Non-exchangeable Conformal Prediction for Temporal Graph Neural Networks.
KDD (2)
Tuo Wang, Jian Kang, Yujun Yan, Adithya Kulkarni, Dawei Zhou
2025 J jnl
Non-exchangeable Conformal Prediction for Temporal Graph Neural Networks.
CoRR
Tuo Wang, Jian Kang, Yujun Yan, Adithya Kulkarni, Dawei Zhou
2024 A* conf
Conformalized Link Prediction on Graph Neural Networks.
KDD
Tianyi Zhao, Jian Kang, Lu Cheng
2024 J jnl
Conformalized Link Prediction on Graph Neural Networks.
CoRR
Tianyi Zhao, Jian Kang, Lu Cheng
2024 A conf
Data Quality-aware Graph Machine Learning.
CIKM
Yu Wang, Kaize Ding, Xiaorui Liu, Jian Kang, Ryan A. Rossi, Tyler Derr
2024 A* conf
Deceptive Fairness Attacks on Graphs via Meta Learning.
ICLR
Jian Kang, Yinglong Xia, Ross Maciejewski, Jiebo Luo, Hanghang Tong
2024 A* conf
Ensuring User-side Fairness in Dynamic Recommender Systems.
WWW
Hyunsik Yoo, Zhichen Zeng, Jian Kang, Ruizhong Qiu, David Zhou, Zhining Liu, Fei Wang, Charlie Xu, Eunice Chan, Hanghang Tong
2024 A* conf
LARP: Language Audio Relational Pre-training for Cold-Start Playlist Continuation.
KDD
Rebecca Salganik, Xiaohao Liu, Yunshan Ma, Jian Kang, Tat-Seng Chua
2024 J jnl
LARP: Language Audio Relational Pre-training for Cold-Start Playlist Continuation.
CoRR
Rebecca Salganik, Xiaohao Liu, Yunshan Ma, Jian Kang, Tat-Seng Chua
2024 J jnl
On the Generalization Capability of Temporal Graph Learning Algorithms: Theoretical Insights and a Simpler Method.
CoRR
Weilin Cong, Jian Kang, Hanghang Tong, Mehrdad Mahdavi
2024 A conf
On the Sensitivity of Individual Fairness: Measures and Robust Algorithms.
CIKM
Xinyu He, Jian Kang, Ruizhong Qiu, Fei Wang, Jose Sepulveda, Hanghang Tong
2024 A* conf
PageRank Bandits for Link Prediction.
NeurIPS
Yikun Ban, Jiaru Zou, Zihao Li, Yunzhe Qi, Dongqi Fu, Jian Kang, Hanghang Tong, Jingrui He
2024 J jnl
PageRank Bandits for Link Prediction.
CoRR
Yikun Ban, Jiaru Zou, Zihao Li, Yunzhe Qi, Dongqi Fu, Jian Kang, Hanghang Tong, Jingrui He
2024 A* conf
Theoretical and Empirical Insights into the Origins of Degree Bias in Graph Neural Networks.
NeurIPS
Arjun Subramonian, Jian Kang, Yizhou Sun
2024 J jnl
Theoretical and Empirical Insights into the Origins of Degree Bias in Graph Neural Networks.
CoRR
Arjun Subramonian, Jian Kang, Yizhou Sun
2024 — conf
TrustLOG: The Second Workshop on Trustworthy Learning on Graphs.
WWW (Companion Volume)
Jingrui He, Jian Kang, Fatemeh Nargesian, Haohui Wang, An Zhang, Dawei Zhou
2023 — conf
BeMap: Balanced Message Passing for Fair Graph Neural Network.
LoG
Xiao Lin, Jian Kang, Weilin Cong, Hanghang Tong
2023 J jnl
BeMap: Balanced Message Passing for Fair Graph Neural Network.
CoRR
Xiao Lin, Jian Kang, Weilin Cong, Hanghang Tong
2023 J jnl
Deceptive Fairness Attacks on Graphs via Meta Learning.
CoRR
Jian Kang, Yinglong Xia, Ross Maciejewski, Jiebo Luo, Hanghang Tong
2023 A* conf
Do We Really Need Complicated Model Architectures For Temporal Networks?
ICLR
Weilin Cong, Si Zhang, Jian Kang, Baichuan Yuan, Hao Wu, Xin Zhou, Hanghang Tong, Mehrdad Mahdavi
2023 J jnl
Do We Really Need Complicated Model Architectures For Temporal Networks?
CoRR
Weilin Cong, Si Zhang, Jian Kang, Baichuan Yuan, Hao Wu, Xin Zhou, Hanghang Tong, Mehrdad Mahdavi
2023 J jnl
Ensuring User-side Fairness in Dynamic Recommender Systems.
CoRR
Hyunsik Yoo, Zhichen Zeng, Jian Kang, Zhining Liu, David Zhou, Fei Wang, Eunice Chan, Hanghang Tong
2022 A* conf
Algorithmic Fairness on Graphs: Methods and Trends.
KDD
Jian Kang, Hanghang Tong
2022 J jnl
FairRankVis: A Visual Analytics Framework for Exploring Algorithmic Fairness in Graph Mining Models.
IEEE Trans. Vis. Comput. Graph.
Tiankai Xie, Yuxin Ma, Jian Kang, Hanghang Tong, Ross Maciejewski
2022 B conf
InfoFair: Information-Theoretic Intersectional Fairness.
IEEE Big Data
Jian Kang, Tiankai Xie, Xintao Wu, Ross Maciejewski, Hanghang Tong
2022 A* conf
JuryGCN: Quantifying Jackknife Uncertainty on Graph Convolutional Networks.
KDD
Jian Kang, Qinghai Zhou, Hanghang Tong
2022 J jnl
JuryGCN: Quantifying Jackknife Uncertainty on Graph Convolutional Networks.
CoRR
Jian Kang, Qinghai Zhou, Hanghang Tong
2022 A* conf
RawlsGCN: Towards Rawlsian Difference Principle on Graph Convolutional Network.
WWW
Jian Kang, Yan Zhu, Yinglong Xia, Jiebo Luo, Hanghang Tong
2022 J jnl
RawlsGCN: Towards Rawlsian Difference Principle on Graph Convolutional Network.
CoRR
Jian Kang, Yan Zhu, Yinglong Xia, Jiebo Luo, Hanghang Tong
2022 A conf
TrustLOG: The First Workshop on Trustworthy Learning on Graphs.
CIKM
Jian Kang, Shuaicheng Zhang, Bo Li, Jingrui He, Jian Pei, Dawei Zhou
2022 B conf
iFiG: Individually Fair Multi-view Graph Clustering.
IEEE Big Data
Yian Wang, Jian Kang, Yinglong Xia, Jiebo Luo, Hanghang Tong
2021 A conf
Fair Graph Mining.
CIKM
Jian Kang, Hanghang Tong
2021 J jnl
Graph Ranking Auditing: Problem Definition and Fast Solutions.
IEEE Trans. Knowl. Data Eng.
Meijia Wang, Jian Kang, Nan Cao, Yinglong Xia, Wei Fan, Hanghang Tong
2021 A* conf
Individual Fairness for Graph Neural Networks: A Ranking based Approach.
KDD
Yushun Dong, Jian Kang, Hanghang Tong, Jundong Li
2021 J jnl
MultiFair: Multi-Group Fairness in Machine Learning.
CoRR
Jian Kang, Tiankai Xie, Xintao Wu, Ross Maciejewski, Hanghang Tong
2020 A* conf
InFoRM: Individual Fairness on Graph Mining.
KDD
Jian Kang, Jingrui He, Ross Maciejewski, Hanghang Tong
2019 A conf
N2N: Network Derivative Mining.
CIKM
Jian Kang, Hanghang Tong
2018 — conf
AURORA: Auditing PageRank on Large Graphs.
IEEE BigData
Jian Kang, Meijia Wang, Nan Cao, Yinglong Xia, Wei Fan, Hanghang Tong
2018 J jnl
AURORA: Auditing PageRank on Large Graphs.
CoRR
Jian Kang, Hanghang Tong, Yinglong Xia, Wei Fan
2018 A conf
X-Rank: Explainable Ranking in Complex Multi-Layered Networks.
CIKM
Jian Kang, Scott Freitas, Haichao Yu, Yinglong Xia, Nan Cao, Hanghang Tong