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ORCIDPeng 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
![[0000-0002-4931-0566]](/%20https://reactormag.com/five-https-dblp.org/img/orcid-mark.12x12.png "0000-0002-4931-0566")
— Chinese Academy of Sciences, Institute of Software, Beijing, China - Peng Wu 0003 — University of Delaware
- Peng Wu 0004 — Fuzhou University, School of Economics and Management, China (and 2 more)
- 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 — Vrije Universiteit Brussel, Department of Electronics and Informatics, Belgium (and 1 more)
- Peng Wu 0009 — University of Connecticut, Department of Computer Science and Engineering, Storrs, CT, USA
- Peng Wu 0010 — Anhui University, School of Mathematical Science, Hefei, China
- Peng Wu 0011 — Curtin University, Department of Construction Management, Perth, Australia
- Peng Wu 0013 — Shanghai Jiao Tong University, Shanghai, China
- Peng Wu 0014 — Shandong University, China
- Peng Wu 0015 — Northwestern Polytechnical University, Xi'an, China
- Peng Wu 0016 — China Electric Power Research Institute, Nanjing, China
- Peng Wu 0017 — Beijing University of Chemical Technology, Beijing, China
- Peng Wu 0018 — Zhejiang University, Hangzhou, China
- Peng Wu 0019 — Northeastern University, Boston, MA, USA
- Peng Wu 0020 — University of Jinan, School of Information Science and Engineering, China (and 1 more)
- Peng Wu 0021 — Wuhan University, School of Electronic Information, China (and 1 more)
- Peng Wu 0022 — Shanghai Jiao Tong University, Biomedical Instrument Institute, School of Biomedical Engineering, China
- Peng Wu 0023 — Chinese Academy of Sciences, Hefei Institutes of Physical Science, Anhui Institute of Optics and Fine Mechanics, China
- Peng Wu 0024 — Chinese Academy of Sciences, Hefei Institutes of Physical Science, Institute of Plasma Physics, China
- Peng Wu 0025 — National University of Defense Technology, College of Intelligence Science and Technology, Changsha, China
- Peng Wu 0026 — Hangzhou Dianzi University, School of Sciences, China (and 1 more)
- Peng Wu 0027 — Beijing Jiaotong University, School of Computer and Information Technology, China
- Peng Wu 0028 — Zhejiang Sci-Tech University, School of Information Science and Engineering, Hangzhou, China (and 2 more)
- Peng Wu 0029 — Zhejiang A&F University, College of Mathematics and Computer Science, Hangzhou, China
- Peng Wu 0030 — University of Electronic Science and Technology of China, Chengdu, Sichuan, China
- Peng Wu 0031 — National Innovation Institute of Defense Technology, Academy of Military Science, Beijing, China
- Peng Wu 0032 — Nanjing University of Science & Technology, Nanjing, Jiangsu, China
- Peng Wu 0033 — University College London, London, UK
- Peng Wu 0034 — Jilin University, Changchun, China
- Peng Wu 0035 — Purdue University, West Lafayette, IN, USA
- Peng Wu 0036 — Sichuan Tourism University, Chengdu, China
- Peng Wu 0037 — Nanjing University, Nanjing, China
Other persons with a similar name
- Wu Peng
- Wuliang Peng (aka: Wu-Liang Peng) — disambiguation page
- Chih-Peng Wu
- Ji-Peng Wu
- Peng-Jung Wu
- Peng-Ling Wu (aka: Pengling Wu)
- Peng-Yi Wu
- Pengfei Wu (aka: Peng-Fei Wu) — disambiguation page
- Ben Wu 0001 (aka: Ben P. Wu 0001, Ben Peng Wu 0001) — University of Sheffield, School of Computer Science, UK
- Pengfei Wu 0005 (aka: Peng-Fei Wu 0005) — Nanjing University of Posts and Telecommunications, School of Computer Science, China
- show all similar names
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2020 – today
- 2026
[c27]Xueqing Liu, Qinwei Yang, Zhiyu Hao, Peng Wu:
Offline Policy Enhancement and Transfer by Combining Experimental and External One-Sided Treatment Data. KDD (1) 2026: 927-936- [c26]Shengjia Zhang, Weiqin Yang, Jiawei Chen, Peng Wu, Yuegang Sun, Gang Wang, Qihao Shi, Can Wang:
Talos: Optimizing Top-K Accuracy in Recommender Systems. WWW 2026: 6666-6677 - [i19]Shengjia Zhang, Weiqin Yang, Jiawei Chen, Peng Wu, Yuegang Sun, Gang Wang, Qihao Shi, Can Wang:
Talos: Optimizing Top-K Accuracy in Recommender Systems. CoRR abs/2601.19276 (2026) - 2025
- [j1]Hang Pan, Shuxian Bi, Wenjie Wang, Haoxuan Li, Peng Wu, Fuli Feng:
Proactive Recommendation in Social Networks: Steering user interest with causal inference. AI Open 6: 130-141 (2025) - [c25]Xueqing Liu, Qinwei Yang, Zhaoqing Tian, Ruocheng Guo, Peng Wu:
Optimal Policy Adaptation Under Covariate Shift. IJCAI 2025: 5797-5805 - [c24]Weiqin Yang, Jiawei Chen, Shengjia Zhang, Peng Wu, Yuegang Sun, Yan Feng, Chun Chen, Can Wang:
Breaking the Top-K Barrier: Advancing Top-K Ranking Metrics Optimization in Recommender Systems. KDD (2) 2025: 3542-3552 - [c23]Peng Wu, Haoxuan Li, Chunyuan Zheng, Yan Zeng, Jiawei Chen, Yang Liu, Ruocheng Guo, Kun Zhang:
Learning Counterfactual Outcomes Under Rank Preservation. NeurIPS 2025 - [i18]Xueqing Liu, Qinwei Yang, Zhaoqing Tian, Ruocheng Guo, Peng Wu:
Optimal Policy Adaptation under Covariate Shift. CoRR abs/2501.08067 (2025) - [i17]Peng Wu, Haoxuan Li, Chunyuan Zheng, Yan Zeng, Jiawei Chen, Yang Liu, Ruocheng Guo, Kun Zhang:
Learning Counterfactual Outcomes Under Rank Preservation. CoRR abs/2502.06398 (2025) - [i16]Qinwei Yang, Ruocheng Guo, Shasha Han, Peng Wu:
Identification and Estimation of Long-Term Treatment Effects with Monotone Missing. CoRR abs/2504.19527 (2025) - [i15]Yan Zeng, Shenglan Nie, Feng Xie, Libo Huang, Peng Wu, Zhi Geng:
Confounded Causal Imitation Learning with Instrumental Variables. CoRR abs/2507.17309 (2025) - [i14]Weiqin Yang, Jiawei Chen, Shengjia Zhang, Peng Wu, Yuegang Sun, Yan Feng, Chun Chen, Can Wang:
Breaking the Top-K Barrier: Advancing Top-K Ranking Metrics Optimization in Recommender Systems. CoRR abs/2508.05673 (2025) - [i13]Jiayi Guo, Haoxuan Li, Ye Tian, Peng Wu:
A Relative Error-Based Evaluation Framework of Heterogeneous Treatment Effect Estimators. CoRR abs/2510.16419 (2025) - 2024
- [c22]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 - [c21]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 - [c20]Haoxuan Li, Chunyuan Zheng, Yanghao Xiao, Peng Wu, Zhi Geng, Xu Chen, Peng Cui:
Debiased Collaborative Filtering with Kernel-Based Causal Balancing. ICLR 2024 - [c19]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: 29448-29460 - [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: 53817-53846 - [c17]Feng Xie, Zheng Li, Peng Wu, Yan Zeng, Chunchen Liu, Zhi Geng:
Local Causal Structure Learning in the Presence of Latent Variables. ICML 2024: 54511-54530 - [c16]Qinwei Yang, Xueqing Liu, Yan Zeng, Ruocheng Guo, Yang Liu, Peng Wu:
Learning the Optimal Policy for Balancing Short-Term and Long-Term Rewards. NeurIPS 2024 - [c15]Jiaju Chen, Wenjie Wang, Chongming Gao, Peng Wu, Jianxiong Wei, Qingsong Hua:
Treatment Effect Estimation for User Interest Exploration on Recommender Systems. SIGIR 2024: 1861-1871 - [i12]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) - [i11]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) - [i10]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) - [i9]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) - [i8]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) - [i7]Hang Pan, Shuxian Bi, Wenjie Wang, Haoxuan Li, Peng Wu, Fuli Feng, Xiangnan He:
Proactive Recommendation in Social Networks: Steering User Interest via Neighbor Influence. CoRR abs/2409.08934 (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, Chunyuan Zheng, Peng Wu, Kun Kuang, Yue Liu, Peng Cui:
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, Yang Zhang, Haoxuan Li, Peng Wu, Fuli Feng, Xiangnan He:
Causal Recommendation: Progresses and Future Directions. SIGIR 2023: 3432-3435 - [c5]Haoxuan Li, Yanghao Xiao, Chunyuan Zheng, Peng Wu:
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, Rui Zhang, Xiao-Hua Zhou:
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, Rui Zhang, Rui Zhang, Jie Sun:
A Generalized Doubly Robust Learning Framework for Debiasing Post-Click Conversion Rate Prediction. KDD 2022: 252-262 - [c2]Sihao Ding, Peng Wu, Fuli Feng, Yitong Wang, Xiangnan He, Yong Liao, Yongdong Zhang:
Addressing Unmeasured Confounder for Recommendation with Sensitivity Analysis. KDD 2022: 305-315 - [c1]Riccardo Tommasini, Senjuti Basu Roy, Xuan Wang, Hongwei Wang, Heng Ji, Jiawei Han, Preslav Nakov, Giovanni Da San Martino, Firoj Alam, Markus Schedl, Elisabeth Lex, Akash Bharadwaj, Graham Cormode, Milan Dojchinovski, Jan Forberg, Johannes Frey, Pieter Bonte, Marco Balduini, Matteo Belcao, Emanuele Della Valle, Junliang Yu, Hongzhi Yin, Tong Chen, Haochen Liu, Yiqi Wang, Wenqi Fan, Xiaorui Liu, Jamell Dacon, Lingjuan Lyu, Jiliang Tang, Aristides Gionis, Stefan Neumann, Bruno Ordozgoiti, Simon Razniewski, Hiba Arnaout, Shrestha Ghosh, Fabian M. Suchanek, Lingfei Wu, Yu Chen, Yunyao Li, Bang Liu, Filip Ilievski, Daniel Garijo, Hans Chalupsky, Pedro A. Szekely, Ilias Kanellos, Dimitris Sacharidis, Thanasis Vergoulis, Nurendra Choudhary, Nikhil Rao, Karthik Subbian, Srinivasan H. Sengamedu, Chandan K. Reddy, Friedhelm Victor, Bernhard Haslhofer, George Katsogiannis-Meimarakis, Georgia Koutrika, Shengmin Jin, Danai Koutra, Reza Zafarani, Yulia Tsvetkov, Vidhisha Balachandran, Sachin Kumar, Xiangyu Zhao, Bo Chen, Huifeng Guo, Yejing Wang, Ruiming Tang, Yang Zhang, Wenjie Wang, Peng Wu, Fuli Feng, Xiangnan He:
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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