Yancheng Yuan

PaulYuan.jpg

Office: TU 821

PolyU

Hong Kong SAR, China

I am an Assistant Professor in Department of Applied Mathematics, The Hong Kong Polytechnic University. I also serve as an Assistant Director of Research Center for Intelligent Operations Research. I was an Assistant Professor (2024.07 – 2025.02) in Department of Data Science and Artificial Intelligence. Before joining PolyU, I was a research fellow in NExT Research Center , School of Computing, National University of Singapore, working with Prof. Tat-Seng CHUA.

I obtained my PhD in Mathematics, from Department of Mathematics, National University of Singapore in 2020. My Ph.D supervisor is Prof. Kim-Chuan TOH. I was fortunately supervised by Prof. Defeng SUN from 2015 to 2018. Prior to NUS, I obtained my Bachelor’s degree in Computational Mathematics from University of Science and Technology of China (USTC) in 2015, where I was supervised by Prof. Juyong ZHANG.

Contact: X + Y, where X = yancheng.yuan, Y = @polyu.edu.hk

Openings : I am looking for postdoctoral fellows with foundation models/model compression/scientific computing backgrounds to join our research group. Please feel free to send me an email with your CV if you are interested.

news

Mar 19, 2025 Our paper Adaptive sieving: A dimension reduction technique for sparse optimization problems has been accepted for publication at Mathematical Programming Computation! :tada:
Feb 24, 2025 Our paper Accelerating Preconditioned ADMM via Degenerate Proximal Point Mappings has been accepted for publication at SIAM Journal on Optimization! :tada:
Jan 28, 2025 We have released a Python package PyClustrPath for solving the convex clustering model with GPU acceleration. User feedbacks and suggestions are warmly welcome!
Jan 23, 2025 Two papers are accepted to ICLR 2025! :tada:

selected publications

  1. MPC
    Adaptive sieving: A dimension reduction technique for sparse optimization problems
    Yancheng Yuan, Meixia Lin , Defeng Sun , and Kim-Chuan Toh
    Mathematical Programming Computation (accepted), 2025
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  2. SIOPT
    Accelerating Preconditioned ADMM via Degenerate Proximal Point Mappings
    Defeng Sun , Yancheng Yuan, Guojun Zhang , and Xinyuan Zhao
    SIAM Journal on Optimization (accepted), 2025
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  3. ICLR
    A Tight Convergence Analysis of Inexact Stochastic Proximal Point Algorithm for Stochastic Composite Optimization Problems
    Shulan Zhu , Chenglong Bao , Defeng Sun , and Yancheng Yuan
    The Thirteenth International Conference on Learning Representations (Accepted), 2025
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  4. SIOPT
    An Efficient Sieving based Secant Method for Sparse Optimization Problems with Least-squares Constraints
    Qian Li , Defeng Sun , and Yancheng Yuan
    SIAM Journal on Optimization, 2024
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  5. ICML
    Collective Certified Robustness against Graph Injection Attacks
    Yuni Lai , Bailin Pan , Kaihuang Chen , Yancheng Yuan, and Kai Zhou
    Proceedings of the 41th International Conference on Machine Learning, 2024
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  6. SIGIR
    LLaRA: Large Language-Recommendation Assistant
    Jiayi Liao , Sihang Li , Zhengyi Yang , Jiancan Wu , Yancheng Yuan, Xiang Wang , and Xiangnan He
    The 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024
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  7. NeurIPS
    Generate What You Prefer: Reshaping Sequential Recommendation via Guided Diffusion
    Zhengyi Yang , Jiancan Wu , Zhicai Wang , Yancheng Yuan, Xiang Wang , and Xiangnan He
    The 37th Conference on Neural Information Processing Systems, 2023
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  8. SIOPT
    A Dimension Reduction Technique for Large-Scale Structured Sparse Optimization Problems with Application to Convex Clustering
    Yancheng Yuan, Tsung-Hui Chang , Defeng Sun , and Kim-Chuan Toh
    SIAM Journal on Optimization, 2022
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  9. JMLR
    Convex Clustering: Model, Theoretical Guarantee and Efficient Algorithm
    Defeng Sun , Kim-Chuan Toh , and Yancheng Yuan
    Journal of Machine Learning Research, 2021
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  10. ICML
    An Efficient Semismooth Newton Based Algorithm for Convex Clustering
    Yancheng Yuan, Defeng Sun , and Kim-Chuan Toh
    Proceedings of the 35th International Conference on Machine Learning, 2018
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