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Peng Wu 0012
Person information
- unicode name: 吴鹏
- affiliation: Beijing Technology and Business University (BTBU), Beijing, China
Other persons with the same name
- Peng Wu — disambiguation page
- Peng Wu 0001 — Meta, USA (and 2 more)
- Peng Wu 0002
— Chinese Academy of Sciences, Institute of Software, Beijing, China
- Peng Wu 0003 — University of Delaware
- Peng Wu 0004
- Peng Wu 0005 — University of California, Santa Barbara, USA
- Peng Wu 0006 — Facebook (and 1 more)
- Peng Wu 0007 — Tsinghua University, Department of Computer Science, TNList, Beijing, China
- Peng Wu 0008
- Peng Wu 0009
- Peng Wu 0010
- Peng Wu 0011
- Peng Wu 0013
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2020 – today
- 2024
- [c21]Honglei Zhang, Shuyi Wang, Haoxuan Li, Chunyuan Zheng, Xu Chen, Li Liu, Shanshan Luo, Peng Wu:
Uncovering the Propensity Identification Problem in Debiased Recommendations. ICDE 2024: 653-666 - [c20]Haoxuan Li, Chunyuan Zheng, Sihao Ding, Peng Wu, Zhi Geng, Fuli Feng, Xiangnan He:
Be Aware of the Neighborhood Effect: Modeling Selection Bias under Interference. ICLR 2024 - [c19]Haoxuan Li, Chunyuan Zheng, Yanghao Xiao, Peng Wu, Zhi Geng, Xu Chen, Peng Cui:
Debiased Collaborative Filtering with Kernel-Based Causal Balancing. ICLR 2024 - [c18]Peng Wu, Ziyu Shen, Feng Xie, Zhongyao Wang, Chunchen Liu, Yan Zeng:
Policy Learning for Balancing Short-Term and Long-Term Rewards. ICML 2024 - [c17]Haoxuan Li, Chunyuan Zheng, Shuyi Wang, Kunhan Wu, Eric Hao Wang, Peng Wu, Zhi Geng, Xu Chen, Xiao-Hua Zhou:
Relaxing the Accurate Imputation Assumption in Doubly Robust Learning for Debiased Collaborative Filtering. ICML 2024 - [c16]Feng Xie, Zheng Li, Peng Wu, Yan Zeng, Chunchen Liu, Zhi Geng:
Local Causal Structure Learning in the Presence of Latent Variables. ICML 2024 - [c15]Jiaju Chen
Treatment Effect Estimation for User Interest Exploration on Recommender Systems. SIGIR 2024: 1861-1871 - [i11]Haoxuan Li, Chunyuan Zheng, Yanghao Xiao, Peng Wu, Zhi Geng, Xu Chen, Peng Cui:
Debiased Collaborative Filtering with Kernel-Based Causal Balancing. CoRR abs/2404.19596 (2024) - [i10]Haoxuan Li, Chunyuan Zheng, Sihao Ding, Peng Wu, Zhi Geng, Fuli Feng, Xiangnan He:
Be Aware of the Neighborhood Effect: Modeling Selection Bias under Interference. CoRR abs/2404.19620 (2024) - [i9]Peng Wu, Ziyu Shen, Feng Xie, Zhongyao Wang, Chunchen Liu, Yan Zeng:
Policy Learning for Balancing Short-Term and Long-Term Rewards. CoRR abs/2405.03329 (2024) - [i8]Jiaju Chen, Wenjie Wang, Chongming Gao, Peng Wu, Jianxiong Wei, Qingsong Hua:
Treatment Effect Estimation for User Interest Exploration on Recommender Systems. CoRR abs/2405.08582 (2024) - [i7]Feng Xie, Zheng Li, Peng Wu, Yan Zeng, Chunchen Liu, Zhi Geng:
Local Causal Structure Learning in the Presence of Latent Variables. CoRR abs/2405.16225 (2024) - 2023
- [c14]Haoxuan Li, Quanyu Dai, Yuru Li, Yan Lyu, Zhenhua Dong, Xiao-Hua Zhou, Peng Wu:
Multiple Robust Learning for Recommendation. AAAI 2023: 4417-4425 - [c13]Haoxuan Li, Yan Lyu, Chunyuan Zheng, Peng Wu:
TDR-CL: Targeted Doubly Robust Collaborative Learning for Debiased Recommendations. ICLR 2023 - [c12]Haoxuan Li, Chunyuan Zheng, Peng Wu:
StableDR: Stabilized Doubly Robust Learning for Recommendation on Data Missing Not at Random. ICLR 2023 - [c11]Haoxuan Li, Yanghao Xiao, Chunyuan Zheng, Peng Wu, Peng Cui:
Propensity Matters: Measuring and Enhancing Balancing for Recommendation. ICML 2023: 20182-20194 - [c10]Haoxuan Li, Chunyuan Zheng, Yixiao Cao, Zhi Geng, Yue Liu, Peng Wu:
Trustworthy Policy Learning under the Counterfactual No-Harm Criterion. ICML 2023: 20575-20598 - [c9]Haoxuan Li
Who Should Be Given Incentives? Counterfactual Optimal Treatment Regimes Learning for Recommendation. KDD 2023: 1235-1247 - [c8]Jinqiu Jin, Haoxuan Li, Fuli Feng, Sihao Ding, Peng Wu, Xiangnan He:
Fairly Recommending with Social Attributes: A Flexible and Controllable Optimization Approach. NeurIPS 2023 - [c7]Haoxuan Li, Kunhan Wu, Chunyuan Zheng, Yanghao Xiao, Hao Wang, Zhi Geng, Fuli Feng, Xiangnan He, Peng Wu:
Removing Hidden Confounding in Recommendation: A Unified Multi-Task Learning Approach. NeurIPS 2023 - [c6]Wenjie Wang
Causal Recommendation: Progresses and Future Directions. SIGIR 2023: 3432-3435 - [c5]Haoxuan Li
Balancing Unobserved Confounding with a Few Unbiased Ratings in Debiased Recommendations. WWW 2023: 1305-1313 - [i6]Haoxuan Li, Yanghao Xiao, Chunyuan Zheng, Peng Wu:
Balancing Unobserved Confounding with a Few Unbiased Ratings in Debiased Recommendations. CoRR abs/2304.09085 (2023) - 2022
- [c4]Peng Wu, Haoxuan Li, Yuhao Deng, Wenjie Hu, Quanyu Dai, Zhenhua Dong, Jie Sun
On the Opportunity of Causal Learning in Recommendation Systems: Foundation, Estimation, Prediction and Challenges. IJCAI 2022: 5646-5653 - [c3]Quanyu Dai, Haoxuan Li, Peng Wu, Zhenhua Dong, Xiao-Hua Zhou
A Generalized Doubly Robust Learning Framework for Debiasing Post-Click Conversion Rate Prediction. KDD 2022: 252-262 - [c2]Sihao Ding
Addressing Unmeasured Confounder for Recommendation with Sensitivity Analysis. KDD 2022: 305-315 - [c1]Riccardo Tommasini, Senjuti Basu Roy, Xuan Wang
Accepted Tutorials at The Web Conference 2022. WWW (Companion Volume) 2022: 391-399 - [i5]Peng Wu, Haoxuan Li, Yuhao Deng, Wenjie Hu, Quanyu Dai, Zhenhua Dong, Jie Sun, Rui Zhang, Xiao-Hua Zhou:
Causal Analysis Framework for Recommendation. CoRR abs/2201.06716 (2022) - [i4]Yan Lyu, Sunhao Dai, Peng Wu, Quanyu Dai, Yuhao Deng, Wenjie Hu, Zhenhua Dong, Jun Xu, Shengyu Zhu, Xiao-Hua Zhou:
A Semi-Synthetic Dataset Generation Framework for Causal Inference in Recommender Systems. CoRR abs/2202.11351 (2022) - [i3]Peng Wu, Haoxuan Li, Yan Lyu, Xiao-Hua Zhou:
Doubly Robust Collaborative Targeted Learning for Recommendation on Data Missing Not at Random. CoRR abs/2203.10258 (2022) - [i2]Haoxuan Li, Chunyuan Zheng, Xiao-Hua Zhou, Peng Wu:
Stabilized Doubly Robust Learning for Recommendation on Data Missing Not at Random. CoRR abs/2205.04701 (2022) - [i1]Quanyu Dai, Haoxuan Li, Peng Wu, Zhenhua Dong, Xiao-Hua Zhou, Rui Zhang, Rui Zhang, Jie Sun:
A Generalized Doubly Robust Learning Framework for Debiasing Post-Click Conversion Rate Prediction. CoRR abs/2211.06684 (2022)
Coauthor Index
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last updated on 2024-10-08 21:29 CEST by the dblp team
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