Shuang Qiu I am currently a postdoc in the Department of Mathematics at the Hong Kong University of Science and Technology, working with Prof. Tong Zhang. I was a postdoc at the University of Chicago, working with Prof. Mladen Kolar and Prof. Zhaoran Wang. I received my Ph.D. degree in Computer Science and Engineering from the University of Michigan, Ann Arbor in 2021, advised by Prof. Jieping Ye. Previously, I did my internship at Tencent AI Lab, Seattle in 2018, working with Dr. Ji Liu.



Research Interest

My recent research interest generally focuses on solving the decision-making problems. Specifically, I am interested in reinforcement learning and games, optimization, and statistical learning from the theoretical perspective. In addition, I am also interested in the application of machine learning to the various areas such as econometrics, computer vision, and data mining.
  • Reinforcement Learning and Games
  • Optimization
  • Statistical Learning
  • Applications in Econometrics, Computer Vision, and Data Mining


News

*NEW* (01/2023) One paper got accepted to ICLR 2023

*NEW* (12/2022) One paper got accepted to AAAI 2023

*NEW* (07/2022) I will be serving as Senior Program Committee (SPC) member in AAAI 2023

*NEW* (05/2022) One paper got accepted to ICML 2022




Selected Recent Publication [Full List]


Optimistic Exploration with Learned Features Provably Solves Markov Decision Processes with Neural Dynamics
Sirui Zheng, Lingxiao Wang, Shuang Qiu, Zhuoran Yang, Csaba Szepesvari, Zhaoran Wang
International Conference on Learning Representations (ICLR), 2023
[PDF] 


Gradient-Variation Bound for Online Convex Optimization with Constraints
Shuang Qiu, Xiaohan Wei, Mladen Kolar
AAAI Conference on Artificial Intelligence (AAAI), 2023
[PDF] 


Contrastive UCB: Provably Efficient Contrastive Self-Supervised Learning in Online Reinforcement Learning
Shuang Qiu, Lingxiao Wang, Chenjia Bai, Zhuoran Yang, Zhaoran Wang
International Conference on Machine Learning (ICML), 2022
[PDF]  [Codes]


In-Database Machine Learning with CorgiPile: Stochastic Gradient Descent without Full Data Shuffle
Lijie Xu, Shuang Qiu, Binhang Yuan, Jiawei Jiang, Cedric Renggli, Shaoduo Gan, Kaan Kara, Guoliang Li, Ji Liu, Wentao Wu,
Jieping Ye, Ce Zhang

International Conference on Management of Data (SIGMOD), 2022
[PDF]  [Extended Version]


On Reward-Free RL with Kernel and Neural Function Approximations: Single-Agent MDP and Markov Game
Shuang Qiu, Jieping Ye, Zhaoran Wang, Zhuoran Yang
International Conference on Machine Learning (ICML), 2021
[PDF]


Provably Efficient Fictitious Play Policy Optimization for Zero-Sum Markov Games with Structured Transitions
Shuang Qiu, Xiaohan Wei, Jieping Ye, Zhaoran Wang, Zhuoran Yang
International Conference on Machine Learning (ICML), 2021
[PDF]


Stylized Neural Painting
Zhengxia Zou, Tianyang Shi, Shuang Qiu, Yi Yuan, Zhenwei Shi
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021
[PDF]  [Codes]  [Project]
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Automatic Image-to-Painting Translation Method Generates Vivid Paintings in Controllable Styles
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Upper Confidence Primal-Dual Reinforcement Learning for CMDP with Adversarial Loss
Shuang Qiu, Xiaohan Wei, Zhuoran Yang, Jieping Ye, Zhaoran Wang
Advances in Neural Information Processing Systems (NeurIPS), 2020
[PDF]


Robust One-Bit Recovery via ReLU Generative Networks: Near-Optimal Statistical Rate and Global Landscape Analysis
Shuang Qiu*, Xiaohan Wei*, Zhuoran Yang
International Conference on Machine Learning (ICML), 2020
[PDF]



Academic Service

Conference
  • AAAI Conference on Artificial Intelligence (AAAI), 2023. Senior Program Committee (SPC) Member

  • International Conference on Learning Representations (ICLR), 2023. Reviewer

  • International Conference on Artificial Intelligence and Statistics (AISTATS), 2023. Reviewer

  • Advances in Neural Information Processing Systems (NeurIPS), 2018-2023. Reviewer

  • International Conference on Machine Learning (ICML), 2021-2023. Reviewer

  • AAAI Conference on Artificial Intelligence (AAAI), 2021. Program Committee Member

  • International Joint Conferences on Artificial Intelligence (IJCAI), 2021-2023. Program Committee Member

  • SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2020, 2023. Reviewer
Journal
  • Journal of Machine Learning Research (JMLR)

  • IEEE Transactions on Information Theory (TIT)

  • IEEE Transactions on Knowledge and Data Engineering (TKDE)

  • IEEE Transactions on Neural Networks and Learning Systems (TNNLS)

  • Springer Machine Learning (ML)