Kay Liu

According to our database, Kay Liu authored at least 15 papers between 2022 and 2024.

Collaborative distances:

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

2024

CoSENT: Consistent Sentence Embedding via Similarity Ranking.

Xiang Huang, Hao Peng, Dongcheng Zou, Zhiwei Liu, Jianxin Li, Kay Liu, Jia Wu, Jianlin Su, Philip S. Yu

IEEE ACM Trans. Audio Speech Lang. Process., 2024

PyGOD: A Python Library for Graph Outlier Detection.

Kay Liu, Yingtong Dou, Xueying Ding, Xiyang Hu, Ruitong Zhang, Hao Peng, Lichao Sun, Philip S. Yu

J. Mach. Learn. Res., 2024

LEGO-Learn: Label-Efficient Graph Open-Set Learning.

Haoyan Xu, Kay Liu, Zhengtao Yao, Philip S. Yu, Kaize Ding, Yue Zhao

CoRR, 2024

BANGS: Game-Theoretic Node Selection for Graph Self-Training.

Fangxin Wang, Kay Liu, Sourav Medya, Philip S. Yu

CoRR, 2024

FedGraph: A Research Library and Benchmark for Federated Graph Learning.

Yuhang Yao, Yuan Li, Xinyi Fan, Junhao Li, Kay Liu, Weizhao Jin, Srivatsan Ravi, Philip S. Yu, Carlee Joe-Wong

CoRR, 2024

Enhancing Fairness in Unsupervised Graph Anomaly Detection through Disentanglement.

Wenjing Chang, Kay Liu, Philip S. Yu, Jianjun Yu

CoRR, 2024

Uncertainty in Graph Neural Networks: A Survey.

Fangxin Wang, Yuqing Liu, Kay Liu, Yibo Wang, Sourav Medya, Philip S. Yu

CoRR, 2024

Overcoming Pitfalls in Graph Contrastive Learning Evaluation: Toward Comprehensive Benchmarks.

Qian Ma, Hongliang Chi, Hengrui Zhang, Kay Liu, Zhiwei Zhang, Lu Cheng, Suhang Wang, Philip S. Yu, Yao Ma

CoRR, 2024

Confidence-aware Fine-tuning of Sequential Recommendation Systems via Conformal Prediction.

Chen Wang, Fangxin Wang, Ruocheng Guo, Yueqing Liang, Kay Liu, Philip S. Yu

CoRR, 2024

Multitask Active Learning for Graph Anomaly Detection.

Wenjing Chang, Kay Liu, Kaize Ding, Philip S. Yu, Jianjun Yu

CoRR, 2024

2023

Data Augmentation for Supervised Graph Outlier Detection with Latent Diffusion Models.

Kay Liu, Hengrui Zhang, Ziqing Hu, Fangxin Wang, Philip S. Yu

CoRR, 2023

Equal Opportunity of Coverage in Fair Regression.

Fangxin Wang, Lu Cheng, Ruocheng Guo, Kay Liu, Philip S. Yu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Benchmarking Node Outlier Detection on Graphs.

Kay Liu, Yingtong Dou, Yue Zhao, Xueying Ding, Xiyang Hu, Ruitong Zhang, Kaize Ding, Canyu Chen, Hao Peng, Kai Shu, Lichao Sun, Jundong Li, George H. Chen, Zhihao Jia, Philip S. Yu

CoRR, 2022

PyGOD: A Python Library for Graph Outlier Detection.

Kay Liu, Yingtong Dou, Yue Zhao, Xueying Ding, Xiyang Hu, Ruitong Zhang, Kaize Ding, Canyu Chen, Hao Peng, Kai Shu, George H. Chen, Zhihao Jia, Philip S. Yu

CoRR, 2022

BOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed Graphs.

Kay Liu, Yingtong Dou, Yue Zhao, Xueying Ding, Xiyang Hu, Ruitong Zhang, Kaize Ding, Canyu Chen, Hao Peng, Kai Shu, Lichao Sun, Jundong Li, George H. Chen, Zhihao Jia, Philip S. Yu

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022