Yu-Jie Zhang @ SYI Lab, Utokyo

Ph.D. Student, Sugiyama-Yokoya-Ishida Lab
Department of Complexity Science and Engineering
Graduate School of Frontier Sciences
The University of Tokyo, Chiba, Japan

Email: yujie.zhang [at] ms.k.u-tokyo.ac.jp
Supervisor: Prof. Masashi Sugiyama.

[CV, Google Scholar, Github]
zhangyj_photo1.jpg 

About Me

I am a third year Ph.D. student of Department of Complexity Science and Engineering in the University of Tokyo and a member of SYI Lab. I also work as a research assistant on Beyond AI. Previously, I got my M.Sc. degree with the LAMDA Group, Nanjing University in June 2021 under the supervision of Prof. Zhi-Hua Zhou.

Research Interests

My research interests include Machine Learning and Data Mining. Currently, I am interested in


Preprints

Conference Papers

  • Adapting to Continuous Covariate Shift via Online Density Ratio Estimation. [PDF, 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. Page: 29074-29113.

  • Online (Multinomial) Logistic Bandit: Improved Regret and Constant Computation Cost. [PDF, bibtex] (Spotlight)
    Yu-Jie Zhang and Masashi Sugiyama.
    In: Advances in Neural Information Processing Systems 36 (NeurIPS 2023), New Orleans, Louisiana, 2023. Page: 29741-29782.

  • Imitation Learning from Vague Feedback. [PDF, bibtex]
    Xin-Qiang Cai, Yu-Jie Zhang, Chao-Kai Chiang and Masashi Sugiyama.
    In: Advances in Neural Information Processing Systems 36 (NeurIPS 2023), New Orleans, Louisiana, 2023. Page: 48275-48292.

  • Adapting to Online Label Shift with Provable Guarantees. [PDF, arXiv, code, bibtex]
    Yong Bai*, Yu-Jie Zhang*, Peng Zhao, Masashi Sugiyama, and Zhi-Hua Zhou. (* indicates equal contribution)
    In: Advances in Neural Information Processing Systems 35 (NeurIPS 2022), New Orleans, Louisiana, 2022. Page: 29960-29974.

  • Adaptive Learning for Weakly Labeled Streams. [PDF, code, bibtex]
    Zhen-Yu Zhang, Yu-Yang Qian, Yu-Jie Zhang, Yuan Jiang, Zhi-Hua Zhou.
    In: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022), Washington, DC, 2022.

  • Towards Enabling Learnware to Handle Unseen Jobs. [PDF, code, bibtex]
    Yu-Jie Zhang, Yu-Hu Yan, Peng Zhao and Zhi-Hua Zhou.
    In: Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI 2021), online, 2021. Page: 10964-10972.

  • Exploratory Machine Learning with Unknown Unknowns.[PDF, code, bibtex]
    Peng Zhao, Yu-Jie Zhang and Zhi-Hua Zhou.
    In: Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI 2021), online, 2021. Page: 10999-11006.

  • An Unbiased Risk Estimator for Learning with Augmented Classes.[PDF, arXiv, code, bibtex]
    Yu-Jie Zhang, Peng Zhao, Lanjihong Ma and Zhi-Hua Zhou.
    In: Advances in Neural Information Processing Systems 33 (NeurIPS 2020), online, 2020. Page: 10247-10258.

  • Dynamic Regret of Convex and Smooth Functions.[PDF, arXiv, bibtex]
    Peng Zhao, Yu-Jie Zhang, Lijun Zhang and Zhi-Hua Zhou.
    In: Advances in Neural Information Processing Systems 33 (NeurIPS 2020), online, 2020. Page: 12510-12520.

  • A Simple Online Algorithm for Competing with Dynamic Comparators. [PDF, bibtex, slide]
    Yu-Jie Zhang, Peng Zhao, and Zhi-Hua Zhou.
    In: Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI 2020), online, 2020.

Journal Paper

  • Adaptivity and Non-stationarity: Problem-dependent Dynamic Regret for Online Convex Optimization. [PDF, arXiv, bibtex]
    Peng Zhao, Yu-Jie Zhang, Lijun Zhang, and Zhi-Hua Zhou.
    Journal of Machine Learning Research (JMLR), to appear, 2024.

  • Exploratory Machine Learning with Unknown Unknowns. [PDF, code, bibtex]
    Peng Zhao, Jia-Wei Shan, Yu-Jie Zhang and Zhi-Hua Zhou.
    Artificial Intelligence (AIJ), to appear, 2024.

Academic Service

  • Reviewer for Conferences: AAAI (2021, 2024), AISTATS (2021, 2022, 2023, 2024), ECAI (2020), ICLR (2022, 2023, 2024), ICML (2022, 2023, 2024), IJCAI (2020, 2021, 2022, 2023), NeurIPS (2021, 2022, 2023), UAI (2022, 2023, 2024)
  • Reviewer for Journals: JMLR, IEEE TPAMI, FCS

Awards & Honors

  • NeurIPS 2023 Top Reviewer, 2023
  • UAI 2023 Top Reviewer, 2023
  • NeurIPS 2022 Top Reviewer, 2022
  • Todai Fellowship, 2021
  • Excellent Graduate of Nanjing University, Nanjing, 2021
  • National Graduate Scholarship for Master Student, MOE of PRC, 2020
  • Excellent Graduate of Tongji University, Shanghai, 2018
  • Shanghai Undergraduate Scholarship, Shanghai, 2017, 2016