Yu-Jie Zhang @ SYI Lab, Utokyo
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
- Online Learning and Sequential Prediction
- Supervised Learning with Distribution Change
- Weakly Supervised Learning
Preprints
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Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization. [conference version, long version, arXiv, bibtex]
Sijia Chen, Yu-Jie Zhang, Wei-Wei Tu, Peng Zhao, and Lijun Zhang.
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Adaptivity and Non-stationarity: Problem-dependent Dynamic Regret for Online Convex Optimization. [arXiv]
Peng Zhao, Yu-Jie Zhang, Lijun Zhang, and Zhi-Hua Zhou.
Publications
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Adapting to Continuous Covariate Shift via Online Density Ratio Estimation. [PDF,arXiv]
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 to appear.
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Online (Multinomial) Logistic Bandit: Improved Regret and Constant Computation Cost. [PDF forthcoming] (Spotlight)
Yu-Jie Zhang and Masashi Sugiyama.
In: Advances in Neural Information Processing Systems 36 (NeurIPS 2023), New Orleans, Louisiana, 2023. Page to appear.
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Imitation Learning from Vague Feedback. [PDF forthcoming]
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 to appear.
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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.
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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'22), Washington, DC, 2022.
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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.
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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.
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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.
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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.
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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.
Academic Service
- Reviewer for Conferences: AAAI (2021,2024), AISTATS (2021, 2022, 2023,2024), ECAI (2020), ICLR (2022, 2023,2024), ICML (2022,2023), IJCAI (2020, 2021, 2022, 2023), NeurIPS (2021, 2022 top reviewer, 2023), UAI (2022, 2023 top reviewer)
- Reviewer for Journals: IEEE TPAMI, FCS
Awards & Honors
- 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