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Xiao Zhang

Tenure-Track Assistant Professor, Gaoling School of Artificial Intelligence, Renmin University of China

e-mail：zhangx89@ruc.edu.cn

Chinese Homepage

PERSONAL PROFILE

Xiao Zhang is a tenure-track assistant professor at Gaoling School of Artificial Intelligence, Renmin University of China. He was a post-doc researcher at GSAI, Renmin University of China from 2020 to 2022, supervised by Ji-Rong Wen. He received his Ph.D. in College of Intelligence and Computing from Tianjin University, in 2019, supervised by Shizhong Liao. His research interests include online learning, causal learning, information retrieval and model selection. He has published over 20 papers on top-tier conferences and journals in artificial intelligence, e.g., ICML, KDD, SIGIR, AAAI, IJCAI, WWW, CIKM, etc.

RESEARCH INTERESTS

  • Key Words: Online learning; Causal learning; Turstworthy machine learning; Information retrieval; Model selection.

  • Research Interests: Dr. Xiao Zhang's group focuses on developing accountable, controllable and efficient online machine learning theory and algorithm in sequential prediction/decision scenarios, especially the new paradigm of causal machine learning. They aim to develop useful and robust machine learning algorithms in information retrieval applications.

WORK EXPERIENCE

  • 2022-present, Renmin University of China, Assistant Professor.
  • 2020-2022, Renmin University of China, Postdoctoral Researcher. Supervisor: Prof. Ji-Rong Wen.

EDUCATION

  • 2015-2019，Tianjin University, Ph.D., Computer Application Technology, Advisor: Prof. Shizhong Liao.
  • 2012-2015, Northwestern Polytechnical University, M.S., Computing Mathematics, Advisor: Prof. Quan Lu.
  • 2008-2012，Shanxi University, B.Sc., Information and Computing Sciences.

TEACHING

  • Advanced Reinforcement Learning (Fall Semester 2022)
  • Mining the Massive Data (Spring Semester 2022, 2023, with Dr. Yong Liu)

PREPRINT PAPERS

Xiao Zhang, Ninglu Shao, Zihua Si, Jun Xu, Wenha Wang, Hanjing Su, Ji-Rong Wen. Partial information as full: Reward imputation with sketching in bandits, https://doi.org/10.48550/arXiv.2210.06719

Zhongxiang Sun, Jun Xu, Xiao Zhang, Zhenhua Dong, Ji-Rong Wen. Law article-enhanced legal case matching: A model-agnostic causal learning approach, https://arxiv.org/abs/2210.11012

REPRESENTATIVE PAPERS

Chen Xu, Sirui Chen, Jun Xu, Weiran Shen, Xiao Zhang, Gang Wang, Zhenhua Dong. P-MMF: Provider max-min fairness re-ranking in recommender system. Proceedings of the Web Conference 2023 (WWW 2023), 2023, accepted.

Zihua Si, Zhongxiang Sun, Xiao Zhang, Jun Xu, Yang Song, Xiaoxue Zang, Ji-Rong Wen. Enhancing recommendation with search data in a causal learning manner. ACM Transactions on Information Systems (TOIS), 2023, accepted.

Haiyuan Zhao, Jun Xu, Xiao Zhang, Guohao Cai, Zhenhua Dong, Ji-Rong Wen. Separating examination and trust bias from click predictions for unbiased relevance ranking. Proceedings of the 16th ACM International Conference on Web Search and Data Mining (WSDM 2023), accepted.

Haonan Jia, Xiao Zhang, Jun Xu, Wei Zeng, Hao Jiang, Xiaohui Yan. Variance reduction for deep Q-Learning using stochastic recursive gradient, Proceedings of the 29th International Conference on Neural Information Processing (ICONIP 2022), accepted.

Xiao Zhang, Sunhao Dai, Jun Xu, Zhenhua Dong, Quanyu Dai, Ji-Rong Wen. Counteracting user attention bias in music streaming recommendation via reward modification. Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022), 2504–2514, 2022.

Zihua Si, Xueran Han, Xiao Zhang, Jun Xu, Yue Yin, Yang Song, Ji-Rong Wen. A model-agnostic causal learning framework for recommendation using search data. Proceedings of the Web Conference 2022 (WWW 2022), 224–233, 2022.

Xiao Zhang, Haonan Jia, Hanjing Su, Wenhan Wang, Jun Xu, Ji-Rong Wen. Counterfactual reward modification for streaming recommendation with delayed feedback. Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2021), 41-50, 2021.

Xiao Zhang, Shizhong Liao, Jun Xu, Ji-Rong Wen. Regret bounds for online kernel selection in continuous kernel space. Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI 2021), 10931-10938, 2021.

Xiao Zhang, Shizhong Liao. Hypothesis sketching for online kernel selection in continuous kernel space. Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI 2020), 2498–2504, 2020.

Xiao Zhang, Shizhong Liao. Incremental randomized sketching for online kernel learning. Proceedings of the 36th International Conference on Machine Learning (ICML 2019), 7394–7403, 2019.

Shizhong Liao, Xiao Zhang*. Online kernel selection via tensor sketching. Proceedings of the 28th ACM International Conference on Information and Knowledge Management (CIKM 2019), 801–810, 2019.

Xiao Zhang, Shizhong Liao. Online kernel selection via incremental sketched kernel alignment. Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI 2018), 3118–3124, 2018.

Xiao Zhang, Shizhong Liao. Tensor completion via multi-shared-modes canonical correlation analysis. Neurocomputing, 205: 106–115, 2016.

Xiao Zhang, Yun Liao, Shizhong Liao. A survey on online kernel selection for online kernel learning. WIREs Data Mining and Knowledge Discovery, 9(2): e1295, 2019.

Shan Xu, Xiao Zhang, Shizhong Liao. New online kernel ridge regression via incremental predictive sampling. Proceedings of the 28th ACM International Conference on Information and Knowledge Management (CIKM 2019), 791–800, 2019.

Shan Xu, Xiao Zhang, Shizhong Liao. A linear incremental Nystrom method for online kernel learning. Proceedings of the 24th International Conference on Pattern Recognition (ICPR 2018), 2256–2261, 2018. (Best Student Paper)