TaylorS: A Multi-Order Expansion Structure for Urban Spatio-Temporal Forecasting (Code)
IEEE TKDE, 2025
Jianyang Qin(PhD), Yan Jia, Binxing Fang, Qing Liao*
CGoFed: Constrained Gradient Optimization Strategy for Federated Class Incremental Learningg (Code)
IEEE TKDE, 2025
Jiyuan Feng(PhD), Xu Yang, Liwen Liang, Weihong Han, Binxing Fang, Qing Liao*
Adaptive Data and Task Joint Scheduling for Multi-Task Learning (Code)
ICDE, 2025
Zeyu Liu(Master), Heyan Chai, Chaoyang Li, Lingzhi Wang, Qing Liao*
Joint Scheduling of Causal Prompts and Tasks for Multi-Task Learning
CVPR, 2025
Chaoyang Li(PhD), Jianyang Qin, Jinhao Cui, Zeyu Liu, Ning Hu, Qing Liao*
Multi-Task Causal Contrastive Learning
IEEE TNNLS, 2025
Chaoyang Li(PhD), Heyan Chai, Jianyang Qin, Ning Hu, Qing Liao*
FedCSR: A Federated Framework for Multi-Platform Cross-Domain Sequential Recommendation with Dual Contrastive Learning (Code)
COLING, 2025
Dongyi Zheng(PhD), Hongyu Zhang, Jianyang Zhai, Zhong Lin, Lingzhi Wang, Jiyuan Feng, Yonghong Tian, Nong Xiao, Qing Liao*
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 Chai(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*