Man-Chung Yue

Assistant Professor

Department of Applied Mathematics

The Hong Kong Polytechnic University


Mathematics, rightly viewed, possesses not only truth, but supreme beauty.
Bertrand Russell


About Me

I am currently an Assistant Professor at Department of Applied Mathematics, The Hong Kong Polytechnic University. From 2017 to 2019, I was a postdoc at Imperial College London, working with Wolfram Wiesemann. I received my Ph.D. in Systems Engineering and Engineering Management under the supervision of Anthony Man-Cho So in 2017 and B.Sc. in Mathematics in 2012, both from The Chinese University of Hong Kong. Here is my Google Scholar page.

Research Interests

My research focuses on continuous optimization and its applications in machine learning, operations research, data science and signal processing. I am particularly interested in the following topics.

Recruitment

The following positions are available. For more information about the positions and/or about the research topics, please send me an email.

Ph.D./M.Phil. Student

I am looking for a self-motivated and hard-working Ph.D./M.Phil. student to work on optimization research topics. The student should possess a bachelor or master degree in a related discipline (e.g., Mathematics, Computer Science, Systems/Industrial Engineering, Electrical Engineering, Machine Learning/Data Science, Physics, etc.) and a solid background in mathematics.

Post-doctoral Researcher

A post-doctoral research position in the area of optimization is available. The applicant should possess a Ph.D. degree in a related discipline (e.g., Mathematics, Computer Science, Systems/Industrial Engineering, Electrical Engineering, Machine Learning/Data Science, Physics, etc.) and a proven research record. The position is full-time and for 2 years.

Publications

Preprints

  1. Man-Chung Yue, Daniel Kuhn, Wolfram Wiesemann. On Linear Optimization over Wasserstein Balls. Submitted, 2020.
  2. Rujun Jiang, Man-Chung Yue, Zhishuo Zhou. An Accelerated First-Order Method with Complexity Analysis for Solving Cubic Regularization Subproblems. Submitted, 2019.

Journal Articles

  1. Yin Tat Lee, Man-Chung Yue. Universal Barrier is n-Self-Concordant. To appear in Mathematics of Operations Research, 2020.
  2. Man-Chung Yue, Zirui Zhou, Anthony Man-Cho So. On the Quadratic Convergence of the Cubic Regularization Method under a Local Error Bound Condition. SIAM Journal on Optimization (2019) 29(1):904-932.
  3. Man-Chung Yue, Zirui Zhou, Anthony Man-Cho So. A Family of Inexact SQA Methods for Non-Smooth Convex Minimization with Provable Convergence Guarantees Based on the Luo-Tseng Error Bound Property. Mathematical Programming (2019) 174(1-2):327-358.
  4. Sherry Xue-Ying Ni, Man-Chung Yue, Kam-Fung Cheung, Anthony Man-Cho So. Phase Retrieval via Sensor Network Localization. Journal of the Operations Research Society of China (2019) 7(1):127-146.
  5. Huikang Liu, Man-Chung Yue, Anthony Man-Cho So. On the Estimation Performance and Convergence Rate of the Generalized Power Method for Phase Synchronization. SIAM Journal on Optimization (2017) 27(4):2426-2446.
  6. Man-Chung Yue, Sissi Xiaoxiao Wu, Anthony Man-Cho So. A Robust Design for MISO Physical-Layer Multicasting Over Line-of-Sight Channels. IEEE Signal Processing Letters (2016) 23(7):939 - 943.
  7. Man-Chung Yue, Anthony Man-Cho So. A Perturbation Inequality for Concave Functions of Singular Values and Its Applications in Low-Rank Matrix Recovery. Applied and Computational Harmonic Analysis (2016) 40(2):396-416.

Conference Proceedings

  1. Zengde Deng, Man-Chung Yue, Anthony Man-Cho So. An Efficient Augmented Lagrangian-Based Method for Linear Equality-Constrained Lasso. Proceedings of the 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2020), pp. 5760-5764, 2020.
  2. Viet Anh Nguyen, Soroosh Shafieezadeh-Abadeh, Man-Chung Yue, Daniel Kuhn, Wolfram Wiesemann. Optimistic Distributionally Robust Optimization for Nonparametric Likelihood Approximation. Proceedings of Advances in Neural Information Processing Systems 32 (NeurIPS 2019), pp. 15872-15882, 2019.
  3. Viet Anh Nguyen, Soroosh Shafieezadeh-Abadeh, Man-Chung Yue, Daniel Kuhn, Wolfram Wiesemann. Calculating Optimistic Likelihoods Using (Geodesically) Convex Optimization. Proceedings of Advances in Neural Information Processing Systems 32 (NeurIPS 2019), pp. 13942-13953, 2019.
  4. Huikang Liu, Man-Chung Yue, Anthony Man-Cho So, Wing-Kin Ma. A Discrete First-Order Method for Large-Scale MIMO Detection with Provable Guarantees. Proceedings of the 18th IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC 2017), pp. 669-673, 2017.
  5. Sissi Xiaoxiao Wu, Man-Chung Yue, Wing-Kin Ma, Anthony Man-Cho So. SDR Approximation Bounds for the Robust Multicast Beamforming Problem with Interference Temperature Constraints. Proceedings of the 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2017), pp. 4054-4058, 2017.

Teaching

The Hong Kong Polytechnic University

Imperial College London

The Chinese University of Hong Kong

Contact

TU827 Yip Kit Chuen Building
The Hong Kong Polytechnic University
Hung Hom
Hong Kong
Email: manchung.yue@polyu.edu.hk