Zhen-Yu Zhang, D.Eng. Postdoctoral Researcher, Imperfect Information Learning Team, RIKEN Center for Advanced Intelligence Project. Email: zhen-yu.zhang [at] riken.jp (alternative: zhangzhenyu.gm [at] gmail.com)

About Me

I am a postdoctoral researcher in the Imperfect Information Learning Team at RIKEN Center for Advanced Intelligence Project, led by Professor Masashi Sugiyama. I obtained my Ph.D. degree from the Department of Computer Science and Technology at Nanjing University in 2022, where I was very fortunate to receive guidance from both Professor Yuan Jiang and Professor Zhi-Hua Zhou.

Research Interests

My research interests include topics in machine learning and data mining.
Most recently, I am interested in:

• Weakly Supervised Learning
• Machine Learning in Non-stationary Environments

Preprint

• On Unsupervised Prompt Learning for Classification with Black-box Language Models. [arXiv]

  Zhen-Yu Zhang, Jiandong Zhang, Huaxiu Yao, Gang Niu, and Masashi Sugiyama.

Publications

• Test-time Adaptation in Non-stationary Environments via Adaptive Representation Alignment. [paper, code, bibtex]

  Zhen-Yu Zhang, Zhiyu Xie, Huaxiu Yao, and Masashi Sugiyama.

  In: Advances in Neural Information Processing Systems 37 (NeurIPS 2024), Vancouver, Canada, 2024.

  
  

• Adapting to Generalized Online Label Shift by Invariant Representation Learning. [paper, code, bibtex]

  Yu-Yang Qian, Yi-Han Wang, Zhen-Yu Zhang, Yuan Jiang, Zhi-Hua Zhou

  In: Proceedings of the 31th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2025), Toronto, Canada, 2025.

  
  

• Achieving Nearly-Optimal Regret and Sample Complexity in Dueling Bandits with Applications in Online Recommendations. [paper, code, bibtex]

  Lanjihong Ma, Yao-Xiang Ding, Zhen-Yu Zhang, Zhi-Hua Zhou

  In: Proceedings of the 31th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2025), Toronto, Canada, 2025.

  
  

• Handling Varied Objectives by Online Decision Making. [paper, code, bibtex]

  Lanjihong Ma, Zhen-Yu Zhang, Yao-Xiang Ding, and Zhi-Hua Zhou.

  In: Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2024), Barcelona, Spain, 2024.

  
  

• Generating Chain-of-Thoughts with a Pairwise-Comparison Approach to Searching for the Most Promising Intermediate Thought. [paper, code, arXiv, bibtex]

  Zhen-Yu Zhang, Siwei Han, Huaxiu Yao, Gang Niu, and Masashi Sugiyama.

  In: Proceedings of the 41st International Conference on Machine Learning (ICML 2024), Vienna, Austria, 2024.

  
  

• Learning with Asynchronous Labels. [paper, code, bibtex]

  Yu-Yang Qian, Zhen-Yu Zhang, Peng Zhao, and Zhi-Hua Zhou.

  ACM Transactions on Knowledge Discovery from Data (TKDD), 2024.

  
  

• Adapting to Continuous Covariate Shift via Online Density Ratio Estimation. [paper, arXiv, bibtex]

  Yu-Jie Zhang, Zhen-Yu Zhang, Peng Zhao, and Masashi Sugiyama.

  In: Advances in Neural Information Processing Systems 36 (NeurIPS 2023), New Orleans, Louisiana, 2023.

  
  

• Handling New Class in Online Label Shift. [paper, code, bibtex]

  Yu-Yang Qian, Yong Bai, Zhen-Yu Zhang, Peng Zhao, and Zhi-Hua Zhou.

  In: Proceedings of the 23rd IEEE International Conference on Data Mining (ICDM 2023), Shanghai, China, 2023.

  
  

• Adaptive Learning for Weakly Labeled Streams. [paper, code, bibtex]

  Zhen-Yu Zhang, Yu-Yang Qian, Yu-Jie Zhang, Yuan Jiang, and Zhi-Hua Zhou.

  In: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022), Washington, DC, 2022.

  
  

• Learning from Incomplete and Inaccurate Supervision. [paper, code, bibtex]

  Zhen-Yu Zhang, Peng Zhao, Yuan Jiang, and Zhi-Hua Zhou.

  IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022.

  
  

• Learning with Feature and Distribution Evolvable Streams. [paper, supp, code, bibtex]

  Zhen-Yu Zhang, Peng Zhao, Yuan Jiang, and Zhi-Hua Zhou.

  In: Proceedings of the 37th International Conference on Machine Learning (ICML 2020), Online, 2020.

  
  

• Safe Deep Semi-Supervised Learning for Unseen-Class Unlabeled Data. [paper, supp, code, bibtex]

  Lan-Zhe Guo, Zhen-Yu Zhang, Yuan Jiang, Yu-Feng Li, and Zhi-Hua Zhou.

  In: Proceedings of the 37th International Conference on Machine Learning (ICML 2020), Online, 2020.

  
  

• Learning from Incomplete and Inaccurate Supervision. [paper, code, bibtex]

  Zhen-Yu Zhang, Peng Zhao, Yuan Jiang, and Zhi-Hua Zhou.

  In: Proceedings of the 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2019), Anchorage, AL, 2019.

  
  

• Regularized Content-Aware Tensor Factorization Meets Temporal-Aware Location Recommendation. [paper, bibtex]

  Defu Lian, Zhen-Yu Zhang, Yong Ge, Fuzheng Zhang, Nicholas Jing Yuan, and Xing Xie.

  In: Proceedings of the 16th IEEE International Conference on Data Mining (ICDM 2016), Barcelona, Spain, 2016.

  
  

Academic Service

• Reviewer for Conferences: ICML (2021-2024); NeurIPS (2021-2024); ICLR (2021-2025); KDD (2022-2025); AAAI (2020-2025); IJCAI (2020-2023); UAI (2023).

• Reviewer for Journals: IEEE TPAMI, IEEE TNNLS, ACM TKDD, MLJ, TMLR.

Awards

• Outstanding Doctoral Dissertation, JSCS, 2023

• Outstanding Doctoral Dissertation, NJU, 2022

• Jiangsu Bank Scholarship, 2021

• National Scholarship for Doctoral Students, MOE of PRC, 2020

• Artificial Intelligence Scholarship, 2019

• Outstanding Bachelor's Thesis, UESTC, 2017