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Haoxuan Li
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On the opportunity of causal learning in recommendation systems: Foundation, estimation, prediction and challenges
P Wu*, H Li*, Y Deng, W Hu, Q Dai, Z Dong, J Sun, R Zhang, XH Zhou
IJCAI (Survey Track) 2022, 2022
712022
StableDR: Stabilized Doubly Robust Learning for Recommendation on Data Missing Not at Random
H Li, C Zheng, P Wu
ICLR 2023, 2023
632023
Optimal transport for treatment effect estimation
H Wang, J Fan, Z Chen, H Li, W Liu, T Liu, Q Dai, Y Wang, Z Dong, ...
NeurIPS 2023, 2024
542024
A generalized doubly robust learning framework for debiasing post-click conversion rate prediction
Q Dai, H Li, P Wu, Z Dong, XH Zhou, R Zhang, R Zhang, J Sun
KDD 2022, 2022
522022
Propensity Matters: Measuring and Enhancing Balancing for Recommendation
H Li, Y Xiao, C Zheng, P Wu, P Cui
ICML 2023, 2023
452023
Balancing unobserved confounding with a few unbiased ratings in debiased recommendations
H Li, Y Xiao, C Zheng, P Wu
WWW 2023, 2023
442023
TDR-CL: Targeted Doubly Robust Collaborative Learning for Debiased Recommendations
H Li, Y Lyu, C Zheng, P Wu
ICLR 2023, 2022
442022
Multiple Robust Learning for Recommendation
H Li*, Q Dai*, Y Li, Y Lyu, Z Dong, XH Zhou, P Wu
AAAI 2023, 2022
382022
Causal recommendation: Progresses and future directions
W Wang, Y Zhang, H Li, P Wu, F Feng, X He
SIGIR (Tutorial) 2023, 2023
312023
Removing hidden confounding in recommendation: a unified multi-task learning approach
H Li, K Wu, C Zheng, Y Xiao, H Wang, Z Geng, F Feng, X He, P Wu
NeurIPS 2023, 2024
302024
Trustworthy Policy Learning under the Counterfactual No-Harm Criterion
H Li, C Zheng, Y Cao, Z Geng, Y Liu, P Wu
ICML 2023, 2023
252023
Debiased collaborative filtering with kernel-based causal balancing
H Li, C Zheng, Y Xiao, P Wu, Z Geng, X Chen, P Cui
ICLR 2024 (Spotlight), 2024
182024
Transfr: Transferable federated recommendation with pre-trained language models
H Zhang, H Liu, H Li, Y Li
arXiv preprint arXiv:2402.01124, 2024
152024
MetaCoCo: A new few-shot classification benchmark with spurious correlation
M Zhang, H Li, F Wu, K Kuang
ICLR 2024, 2024
132024
Who should be given incentives? counterfactual optimal treatment regimes learning for recommendation
H Li, C Zheng, P Wu, K Kuang, Y Liu, P Cui
KDD 2023, 2023
132023
CounterCLR: Counterfactual contrastive learning with non-random missing data in recommendation
J Wang, H Li, C Zhang, D Liang, E Yu, W Ou, W Wang
ICDM 2023, 2023
122023
Uncovering the Propensity Identification Problem in Debiased Recommendations
H Zhang, S Wang, H Li, C Zheng, X Chen, L Liu, S Luo, P Wu
ICDE 2024, 2024
112024
Be Aware of the Neighborhood Effect: Modeling Selection Bias under Interference
H Li, C Zheng, S Ding, P Wu, Z Geng, F Feng, X He
ICLR 2024, 2024
112024
Relaxing the Accurate Imputation Assumption in Doubly Robust Learning for Debiased Collaborative Filtering
H Li, C Zheng, S Wang, K Wu, E Wang, P Wu, Z Geng, X Chen, XH Zhou
ICML 2024 (Spotlight), 2024
102024
Debiased Recommendation with Noisy Feedback
H Li, C Zheng, W Wang, H Wang, F Feng, XH Zhou
KDD 2024, 2024
92024
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Artikler 1–20