Hong Zhu (祝宏)
Hong Zhu (祝宏)
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Noninvasive self-attention for side information fusion in sequential recommendation
C Liu, X Li, G Cai, Z Dong, H Zhu, L Shang
Proceedings of the AAAI Conference on Artificial Intelligence 35 (5), 4249-4256, 2021
Improving Ad Click Prediction by Considering Non-displayed Events
B Yuan, JY Hsia, MY Yang, H Zhu, CY Chang, Z Dong, CJ Lin
Proceedings of the 28th ACM International Conference on Information and …, 2019
Mitigating Confounding Bias in Recommendation via Information Bottleneck
D Liu, P Cheng, H Zhu, Z Dong, X He, W Pan, Z Ming
Fifteenth ACM Conference on Recommender Systems, 351-360, 2021
Towards Open-World Recommendation with Knowledge Augmentation from Large Language Models
Y Xi, W Liu, J Lin, J Zhu, B Chen, R Tang, W Zhang, R Zhang, Y Yu
arXiv preprint arXiv:2306.10933, 2023
Less is better: Unweighted data subsampling via influence function
Z Wang, H Zhu, Z Dong, X He, SL Huang
Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 6340-6347, 2020
Influence function for unbiased recommendation
J Yu, H Zhu, CY Chang, X Feng, B Yuan, X He, Z Dong
Proceedings of the 43rd International ACM SIGIR Conference on Research and …, 2020
OptEmbed: Learning Optimal Embedding Table for Click-through Rate Prediction
F Lyu, X Tang, H Zhu, H Guo, Y Zhang, R Tang, X Liu
Proceedings of the 31st ACM International Conference on Information …, 2022
Counterfactual learning for recommender system
Z Dong, H Zhu, P Cheng, X Feng, G Cai, X He, J Xu, J Wen
Fourteenth ACM Conference on Recommender Systems, 568-569, 2020
Estimating True Post-Click Conversion via Group-stratified Counterfactual Inference
T Gu, K Kuang, H Zhu, J Li, Z Dong, W Hu, Z Li, X He, Y Liu
ADKDD, 2021
One-class Field-aware Factorization Machines for Recommender Systems with Implicit Feedbacks
B Yuan, MY Yang, JY Hsia, H Zhu, Z Liu, Z Dong, CJ Lin
Technical Report. National Taiwan University, 2019
Improving Out-of-Distribution Generalization by Adversarial Training with Structured Priors
Q Wang, Y Wang, H Zhu, Y Wang
NeurIPS 2022, 2022
Debiased Representation Learning in Recommendation via Information Bottleneck
D Liu, P Cheng, H Zhu, Z Dong, X He, W Pan, Z Ming
ACM Transactions on Recommender Systems, 2022
DIWIFT: Discovering Instance-wise Influential Features for Tabular Data
D Liu, P Cheng, H Zhu, X Tang, Y Chen, X Wang, W Pan, Z Ming, X He
Proceedings of the ACM Web Conference 2023, 1673-1682, 2023
Regularization Penalty Optimization for Addressing Data Quality Variance in OoD Algorithms
R Yu, H Zhu, K Li, L Hong, R Zhang, N Ye, SL Huang, X He
Proceedings of the AAAI Conference on Artificial Intelligence 36 (8), 8945-8953, 2022
Collaborative-Enhanced Prediction of Spending on Newly Downloaded Mobile Games under Consumption Uncertainty
P Sun, Y Wang, M Zhang, C Wu, Y Fang, H Zhu, Y Fang, M Wang
Companion Proceedings of the ACM on Web Conference 2024, 10-19, 2024
Contrastive Multi-view Framework for Customer Lifetime Value Prediction
C Wu, J Li, Q Jia, H Zhu, Y Fang, R Tang
arXiv preprint arXiv:2306.14400, 2023
Recommendation model training method, recommendation method, apparatus, and computer-readable medium
CY Chang, H Zhu, D Zhenhua, X He, Y Bowen
US Patent App. 17/242,588, 2021
Confidence-Aware Multi-Field Model Calibration
Y Zhao, C Wu, Q Jia, H Zhu, J Yan, L Zong, L Zhang, Z Dong, M Zhang
arXiv preprint arXiv:2402.17655, 2024
Robust Long-Tailed Learning via Label-Aware Bounded CVaR
H Zhu, R Yu, X Tang, Y Wang, Y Fang, Y Wang
arXiv preprint arXiv:2308.15405, 2023
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