Seguir
Haoran Yang
Haoran Yang
University of Technology Sydney, The Hong Kong Polytechnic University
Dirección de correo verificada de student.uts.edu.au - Página principal
Título
Citado por
Citado por
Año
Hyper meta-path contrastive learning for multi-behavior recommendation
H Yang, H Chen, L Li, SY Philip, G Xu
2021 IEEE International Conference on Data Mining (ICDM), 787-796, 2021
432021
Dual space graph contrastive learning
H Yang, H Chen, S Pan, L Li, PS Yu, G Xu
Proceedings of the ACM Web Conference 2022, 1238-1247, 2022
412022
Graph masked autoencoders with transformers
S Zhang, H Chen, H Yang, X Sun, PS Yu, G Xu
arXiv preprint arXiv:2202.08391, 2022
112022
Generating Counterfactual Hard Negative Samples for Graph Contrastive Learning
H Yang, H Chen, S Zhang, X Sun, Q Li, X Zhao, G Xu
Proceedings of the ACM Web Conference 2023, 621-629, 2023
32023
Graph Data Mining in Recommender Systems
H Chen, Y Li, H Yang
Web Information Systems Engineering–WISE 2021: 22nd International Conference …, 2021
22021
An Empirical Study Towards Prompt-Tuning for Graph Contrastive Pre-Training in Recommendations
H Yang, X Zhao, Y Li, H Chen, G Xu
Advances in Neural Information Processing Systems 36, 2024
12024
Mitigating the performance sacrifice in DP-satisfied federated settings through graph contrastive learning
H Yang, X Zhao, M Li, H Chen, G Xu
Information Sciences 648, 119552, 2023
12023
Being Automated or Not? Risk Identification of Occupations with Graph Neural Networks
D Xu, H Yang, MA Rizoiu, G Xu
International Conference on Advanced Data Mining and Applications, 520-534, 2022
12022
From Occupations to Tasks: A New Perspective on Automatability Prediction Using BERT
D Xu, H Yang, MA Rizoiu, G Xu
2023 10th International Conference on Behavioural and Social Computing (BESC …, 2023
2023
Stage Evolving Graph Neural Network based Dynamic Recommendation with Life Cycles
L Meng, H Yang, J Zhang
2022 International Joint Conference on Neural Networks (IJCNN), 01-08, 2022
2022
El sistema no puede realizar la operación en estos momentos. Inténtalo de nuevo más tarde.
Artículos 1–10