| 2025 | AAAI | Bagging-Expert Network for Multi-Task Learning: A Depolarization Solution in Multi-Gate Mixture-of-Experts. | Gong-Duo Zhang, Ruiqing Chen, Qian Zhao, Zhengwei Wu, Fengyu Han, Huan-Yi Su, Ziqi Liu, Lihong Gu, Lin Zhou |
| 2025 | WSDM | Graph Disentangle Causal Model: Enhancing Causal Inference in Networked Observational Data. | Binbin Hu, Zhicheng An, Zhengwei Wu, Ke Tu, Ziqi Liu, Zhiqiang Zhang, Jun Zhou, Yufei Feng, Jiawei Chen |
| 2024 | CIKM | To Explore or Exploit? A Gradient-informed Framework to Address the Feedback Loop for Graph based Recommendation. | Zhigang Huangfu, Binbin Hu, Zhengwei Wu, Fengyu Han, Gong-Duo Zhang, Lihong Gu, Zhiqiang Zhang |
| 2024 | KDD | DDCDR: A Disentangle-based Distillation Framework for Cross-Domain Recommendation. | Zhicheng An, Zhexu Gu, Li Yu, Ke Tu, Zhengwei Wu, Binbin Hu, Zhiqiang Zhang, Lihong Gu, Jinjie Gu |
| 2024 | KDD | Enhancing Pre-Ranking Performance: Tackling Intermediary Challenges in Multi-Stage Cascading Recommendation Systems. | Jianping Wei, Yujie Zhou, Zhengwei Wu, Ziqi Liu |
| 2024 | WWW | Leave No One Behind: Online Self-Supervised Self-Distillation for Sequential Recommendation. | Shaowei Wei, Zhengwei Wu, Xin Li, Qintong Wu, Zhiqiang Zhang, Jun Zhou, Lihong Gu, Jinjie Gu |
| 2023 | CIKM | Disentangled Interest importance aware Knowledge Graph Neural Network for Fund Recommendation. | Ke Tu, Wei Qu, Zhengwei Wu, Zhiqiang Zhang, Zhongyi Liu, Yiming Zhao, Le Wu, Jun Zhou, Guannan Zhang |
| 2023 | DASFAA | A Scalable Social Recommendation Framework with Decoupled Graph Neural Network. | Ke Tu, Zhengwei Wu, Binbin Hu, Zhiqiang Zhang, Peng Cui, Xiaolong Li, Jun Zhou |
| 2023 | SIGIR | Generative-Contrastive Graph Learning for Recommendation. | Yonghui Yang, Zhengwei Wu, Le Wu, Kun Zhang, Richang Hong, Zhiqiang Zhang, Jun Zhou, Meng Wang |
| 2022 | CIKM | FwSeqBlock: A Field-wise Approach for Modeling Behavior Representation in Sequential Recommendation. | Hao Qian, Qintong Wu, Minghao Li, Zhengwei Wu, Zhiqiang Zhang, Jun Zhou, Lihong Gu, Jinjie Gu |
| 2022 | IJCAI | MERIT: Learning Multi-level Representations on Temporal Graphs. | Binbin Hu, Zhengwei Wu, Jun Zhou, Ziqi Liu, Zhigang Huangfu, Zhiqiang Zhang, Chaochao Chen |
| 2022 | KDD | A Graph Learning Based Framework for Billion-Scale Offline User Identification. | Daixin Wang, Zujian Weng, Zhengwei Wu, Zhiqiang Zhang, Peng Cui, Hongwei Zhao, Jun Zhou |
| 2022 | WWW | A Multi-Task Learning Approach for Delayed Feedback Modeling. | Zhigang Huangfu, Gongduo Zhang, Zhengwei Wu, Qintong Wu, Zhiqiang Zhang, Lihong Gu, Jun Zhou, Jinjie Gu |
| 2021 | AAAI | Joint Incentive Optimization of Customer and Merchant in Mobile Payment Marketing. | Li Yu, Zhengwei Wu, Tianchi Cai, Ziqi Liu, Zhiqiang Zhang, Lihong Gu, Xiaodong Zeng, Jinjie Gu |
| 2020 | KDD | Hubble: An Industrial System for Audience Expansion in Mobile Marketing. | Chenyi Zhuang, Ziqi Liu, Zhiqiang Zhang, Yize Tan, Zhengwei Wu, Zhining Liu, Jianping Wei, Jinjie Gu, Guannan Zhang, Jun Zhou, Yuan Qi |
| 2019 | CogSci | Belief dynamics extraction. | Arun Kumar, Zhengwei Wu, Xaq Pitkow, Paul R. Schrater |
| 2017 | ICNC | Risk index assessment for urban natural gas pipeline leakage based on artificial neural network. | Yang Zhou, Zhengwei Wu |
| 2016 | CISS | Computationally efficient Toeplitz-constrained blind equalization based on independence. | Zhengwei Wu, Saleem A. Kassam |
| 2016 | ICASSP | Relative-gradient Bussgang-type blind equalization algorithms. | Zhengwei Wu, Saleem A. Kassam, Visa Koivunen |
| 2016 | ICDE | Automatic user identification method across heterogeneous mobility data sources. | Wei Cao, Zhengwei Wu, Dong Wang, Jian Li, Haishan Wu |
| 2015 | CISS | Symbol-rate blind equalization based on constrained blind separation. | Zhengwei Wu, Saleem A. Kassam |
| 2014 | ACSSC | Blind equalization based on blind separation with Toeplitz constraint. | Zhengwei Wu, Saleem A. Kassam, Kaipeng Li |
| 2014 | SDM | Laplacian Spectral Properties of Graphs from Random Local Samples. | Zhengwei Wu, Victor M. Preciado |