Associate Professor
wnzhang at sjtu dot edu dot cn
http://wnzhang.net



Weinan Zhang

---

About

Associate Professor (tenure-track)
John Hopcroft Center for Computer Science
and Department of Computer Science and Engineering
Shanghai Jiaotong University

Research Interests

His research interests include machine learning and big data mining, particularly, deep learning and reinforcement learning techniques for real-world data mining scenarios, such as computational advertising, recommender systems, text mining, web search and knowledge graphs.

Selected Publications

Xuejian Wang, Lantao Yu, Kan Ren, Guanyu Tao, Weinan Zhang, Yong Yu, Jun Wang. A Dynamic Attention Deep Model for Article Recommendation by Learning Human Editors’ Demonstration. In the Proceedings of 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. KDD 2017.
Li’ang Yin, Jianhua Han, Weinan Zhang, Yong Yu . Aggregating Crowd Wisdoms with Label-aware Autoencoders. In the Proceedings of IJCAI 2017.
Jun Wang, Lantao Yu, Weinan Zhang, Yu Gong, Yinghui Xu, Benyou Wang, Peng Zhang, Dell Zhang. IRGAN: A Minimax Game for Unifying Generative and Discriminative Information Retrieval Models. In the Proceedings of the 40th annual international ACM SIGIR conference on Research and development in information retrieval. SIGIR 2017.
Shaodian Zhang, Lin Qiu, Frank Chen, Weinan Zhang, Yong Yu and Noemie Elhadad. “We make choices we think are going to save us”: Debate and stance identi?cation for online breast cancer CAM discussions. Proceedings of the 26th International Conference on World Wide Web Companion. WWW 2017.
Shaodian Zhang, Tian Kang, Lin Qiu, Weinan Zhang, Yong Yu and Noemie Elhadad. Cataloguing Treatments Discussed and Used in Online Autism Communities. Proceedings of the 26th International Conference on World Wide Web. WWW 2017.
Lantao Yu, Weinan Zhang, Jun Wang, Yong Yu. SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient. In the Proceedings of 31st AAAI Conference on Arti?cial Intelligence. AAAI 2017.
Fajie Yuan, Guibing Guo, Joemon M. Jose, Long Chen, Haitao Yu, Weinan Zhang. BoostFM: Boosted Factorization Machines for top-N Feature-based Recommendation. Proceedings of the 22nd International Conference on Intelligent User Interfaces. IUI 2017.
Han Cai, Kan Ren, Weinan Zhang, Kleanthis Malialis, Jun Wang, Yong Yu and Defeng Guo. Real-Time Bidding by Reinforcement Learning in Display Advertising. The Tenth ACM International Conference on Web Search and Data Mining. WSDM 2017.
Haifeng Zhang, Weinan Zhang, Yifei Rong, Kan Ren, Wenxin Li, Jun Wang. Managing Risk of Bidding in Display Advertising. The Tenth ACM International Conference on Web Search and Data Mining. WSDM 2017.
Yanru Qu, Han Cai, Kan Ren, Weinan Zhang, Yong Yu, Ying Wen, Jun Wang. Product-based Neural Networks for User Response Prediction. Proceedings of the IEEE 16th International Conference on Data Mining. ICDM 2016.