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Yufei Kuang

PhD Student


yufeikuang@miralab.ai

Interests

  • Learning to Optimize
  • Symbolic Optimization
  • Reinforcement Learning

Education

  • B.S., Statistics, 2020

    Nanjing University

About me

I am currently a master student in USTC. My advisor is Prof. Jie Wang, who leads the MIRA Lab. My research interests include learning to optimize, symbolic optimization, and reinforcement learning.

Awards

  • Excellent Interns, Noah’s Ark Lab (5/400+), 2023

Experience

  • Intern at Noah’s Ark Lab, Huawei Technologies, 2022/06 -

Publications

Yufei Kuang, Jie Wang, Yuyan Zhou, Xijun Li, Fangzhou Zhu, Jianye Hao, Feng Wu. Towards General Algorithm Discovery for Combinatorial Optimization: Learning Symbolic Branching Policy from Bipartite Graph. ICML 2024.

Jie Wang, Zhihai Wang, Xijun Li, Yufei Kuang, Zhihao Shi, Fangzhou Zhu, Mingxuan Yuan, Jia Zeng, Yongdong Zhang, Feng Wu. Learning to Cut via Hierarchical Sequence/Set Model for Efficient Mixed-Integer Programming. TPAMI.

Yufei Kuang, Jie Wang, Haoyang Liu, Fangzhou Zhu, Xijun Li, Jia Zeng, Jianye Hao, Bin Li, Feng Wu. Rethinking Branching on Exact Combinatorial OPtimization Solver: The First Deep Symbolic Discovery Framework. ICLR 2024.

Mingxuan Ye, Yufei Kuang, Jie Wang, Rui Yang, Wengang Zhou, Houqiang Li, Feng Wu. State Sequences Prediction via Fourier Transform for Representation Learning (Spotlight). NeurIPS 2023.

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Zhihai Wang, Xijun Li, Jie Wang, Yufei Kuang, Mingxuan Yuan, Jia Zeng, Yongdong Zhang, Feng Wu. Learning Cut Selection for Mixed-Integer Linear Programming via Hierarchical Sequence Model. ICLR 2023.

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Yufei Kuang, Miao Lu, Jie Wang, Qi Zhou, Bin Li, Houqiang Li. Learning Robust Policy against Disturbance in Transition Dynamics via State-Conservative Policy Optimization. AAAI 2022.

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Qi Zhou, Yufei Kuang, Zherui Qiu, Houqiang Li, Jie Wang. Promoting Stochasticity for Expressive Policies via a Simple and Efficient Regularization Method. NeurIPS 2020.

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