MUSE-Net: Disentangling Multi-Periodicity for Traffic Flow Forecasting (Code)
IEEE ICDE, 2024
Jianyang Qin(PhD), Yan Jia, Yongxin Tong, Heyan Chai, Ye Ding, Xuan Wang, Binxing Fang, Qing Liao*
SGCL: Semantic-aware Graph Contrastive Learning with Lipschitz Graph Augmentation (Code)
IEEE ICDE, 2024
Jinhao Cui(Master), Heyan Chai, Xu Yang, Ye Ding, Binxing Fang, Qing Liao*
Towards Task-Conflicts Momentum-Calibrated Approach for Multi-task Learning (Code)
IEEE ICDE, 2024
Heyan Cha(PhD), Zeyu Liu, Ziyi Yao, Binxing Fang, Qing Liao*
FedDCSR: Federated Cross-domain Sequential Recommendation via Disentangled Representation Learning (Code)
IEEE SDM, 2024
Hongyu Zhang(Master), Dongyi Zheng, Xu Yang, Jiyuan Feng, Qing Liao*
Learning From Easy to Hard: Multi-task Learning With Data Scheduling (Code)
IEEE ICASSP, 2024
Zeyu Liu(Master), Heyan Chai, Qing Liao*
MG-SIN: Multi-Graph Sparse Interaction Network for Multi-Task Stance Detection (Code)
IEEE TNNLS, 2023
Heyan Chai(PhD), Jinhao Cui, Siyu Tang, Ye Ding, Xinwang Liu, Binxing Fang, Qing Liao*
Improving Gradient Trade-offs between Tasks in Multi-task Text Classification (Code)
ACL, 2023
Heyan Chai(PhD), Jin hao Cui, Ye Wang, Min Zhang, Binxing Fang, Qing Liao*
Temporal-Relational Matching Network for Few-shot Temporal Knowledge Graph Completion (Code)
DASFAA, 2023
Xing Gong(Master), Jianyang Qin, Heyan Chai, Ye Ding, Yan Jia, Qing Liao*
FedGR:Federated Learning with Gravitation Regulation for Double Imbalance Distribution (Code)
DASFAA, 2023
Songyue Guo(Master), Xu Yang, Jiyuan Feng, Ye Ding, Wei Wang, Yunqing Feng, Qing Liao*
A Model-Agnostic Approach to Mitigate Gradient Interference for Multi-Task Learning (Code)
IEEE TCYB, 2022
Heyan Chai(PhD), Zhe Yin, Ye Ding, Li Liu, Binxing Fang, Qing Liao*
Affective Knowledge Enhanced Multiple-Graph Fusion Networks for Aspect-based Sentiment Analysis (Code)
EMNLP, 2022
Siyu Tang(Master), Heyan Chai, Ziyi Yao, Ye Ding, Cuiyun Gao, Binxing Fang, Qing Liao*