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Qingyue Zhao

Affiliations:
  • University of California, Department of Computer Science, Los Angeles, CA, USA
  • Tsinghua University, Department of Computer Science and Technology, Beijing, China


According to our database1, Qingyue Zhao authored at least 11 papers between 2024 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
Fast Rates for Offline Contextual Bandits with Forward-KL Regularization under Single-Policy Concentrability.
[BibTeX]
[DOI]
Qingyue Zhao
,
Kaixuan Ji
,
Heyang Zhao
,
Quanquan Gu
CoRR, May, 2026

On the Optimal Sample Complexity of Offline Multi-Armed Bandits with KL Regularization.
[BibTeX]
[DOI]
Kaixuan Ji
,
Qiwei Di
,
Heyang Zhao
,
Qingyue Zhao
,
Quanquan Gu
CoRR, May, 2026

Transformers Trained via Gradient Descent Can Provably Learn a Class of Teacher Models.
[BibTeX]
[DOI]
Chenyang Zhang
,
Qingyue Zhao
,
Quanquan Gu
,
Yuan Cao
CoRR, March, 2026

Near-Optimal Regret for KL-Regularized Multi-Armed Bandits.
[BibTeX]
[DOI]
Kaixuan Ji
,
Qingyue Zhao
,
Heyang Zhao
,
Qiwei Di
,
Quanquan Gu
CoRR, March, 2026

2025
Robust Layerwise Scaling Rules by Proper Weight Decay Tuning.
[BibTeX]
[DOI]
Zhiyuan Fan
,
Yifeng Liu
,
Qingyue Zhao
,
Angela Yuan
,
Quanquan Gu
CoRR, October, 2025

Policy Frameworks for Transparent Chain-of-Thought Reasoning in Large Language Models.
[BibTeX]
[DOI]
Yihang Chen
,
Haikang Deng
,
Kaiqiao Han
,
Qingyue Zhao
CoRR, March, 2025

Global Convergence and Rich Feature Learning in <i>L</i>-Layer Infinite-Width Neural Networks under μP Parametrization.
[BibTeX]
[DOI]
Zixiang Chen
,
Greg Yang
,
Qingyue Zhao
,
Quanquan Gu
CoRR, March, 2025

Nearly Optimal Sample Complexity of Offline KL-Regularized Contextual Bandits under Single-Policy Concentrability.
[BibTeX]
[DOI]
Qingyue Zhao
,
Kaixuan Ji
,
Heyang Zhao
,
Tong Zhang
,
Quanquan Gu
CoRR, February, 2025

Global Convergence and Rich Feature Learning in L-Layer Infinite-Width Neural Networks under μ Parametrization.
[BibTeX]
[DOI]
Zixiang Chen
,
Greg Yang
,
Qingyue Zhao
,
Quanquan Gu
Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024
Towards the Fundamental Limits of Knowledge Transfer over Finite Domains.
[BibTeX]
[DOI]
Qingyue Zhao
,
Banghua Zhu
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Horizon-free Reinforcement Learning in Adversarial Linear Mixture MDPs.
[BibTeX]
[DOI]
Kaixuan Ji
,
Qingyue Zhao
,
Jiafan He
,
Weitong Zhang
,
Quanquan Gu
Proceedings of the Twelfth International Conference on Learning Representations, 2024


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