ManChung 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 ManCho 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.

NonConvex Optimization, NewtonType Methods, Error Bound Theory, Markov Decision Processes, (Distributionally) Robust Optimization
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 selfmotivated and hardworking 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.
Postdoctoral Researcher
A postdoctoral 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 fulltime and for 2 years.
Publications
Preprints

ManChung Yue, Daniel Kuhn, Wolfram Wiesemann.
On Linear Optimization over Wasserstein Balls.
Submitted, 2020.

Rujun Jiang, ManChung Yue, Zhishuo Zhou.
An Accelerated FirstOrder Method with Complexity Analysis for Solving Cubic Regularization Subproblems.
Submitted, 2019.
Journal Articles

Yin Tat Lee, ManChung Yue.
Universal Barrier is nSelfConcordant.
To appear in Mathematics of Operations Research, 2020.

ManChung Yue, Zirui Zhou, Anthony ManCho So.
On the Quadratic Convergence of the Cubic Regularization Method under a Local Error Bound Condition.
SIAM Journal on Optimization (2019) 29(1):904932.

ManChung Yue, Zirui Zhou, Anthony ManCho So.
A Family of Inexact SQA Methods for NonSmooth Convex Minimization with Provable Convergence Guarantees Based on the LuoTseng Error Bound Property.
Mathematical Programming (2019) 174(12):327358.

Sherry XueYing Ni, ManChung Yue, KamFung Cheung, Anthony ManCho So.
Phase Retrieval via Sensor Network Localization.
Journal of the Operations Research Society of China (2019) 7(1):127146.

Huikang Liu, ManChung Yue, Anthony ManCho So.
On the Estimation Performance and Convergence Rate of the Generalized Power Method for Phase Synchronization.
SIAM Journal on Optimization (2017) 27(4):24262446.

ManChung Yue, Sissi Xiaoxiao Wu, Anthony ManCho So.
A Robust Design for MISO PhysicalLayer Multicasting Over LineofSight Channels.
IEEE Signal Processing Letters (2016) 23(7):939  943.

ManChung Yue, Anthony ManCho So.
A Perturbation Inequality for Concave Functions of Singular Values and Its Applications in LowRank Matrix Recovery.
Applied and Computational Harmonic Analysis (2016) 40(2):396416.
Conference Proceedings

Zengde Deng, ManChung Yue, Anthony ManCho So.
An Efficient Augmented LagrangianBased Method for Linear EqualityConstrained Lasso.
Proceedings of the 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2020), pp. 57605764, 2020.

Viet Anh Nguyen, Soroosh ShafieezadehAbadeh, ManChung 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. 1587215882, 2019.

Viet Anh Nguyen, Soroosh ShafieezadehAbadeh, ManChung Yue, Daniel Kuhn, Wolfram Wiesemann.
Calculating Optimistic Likelihoods Using (Geodesically) Convex Optimization.
Proceedings of Advances in Neural Information Processing Systems 32 (NeurIPS 2019), pp. 1394213953, 2019.

Huikang Liu, ManChung Yue, Anthony ManCho So, WingKin Ma.
A Discrete FirstOrder Method for LargeScale MIMO Detection with Provable Guarantees.
Proceedings of the 18th IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC 2017), pp. 669673, 2017.

Sissi Xiaoxiao Wu, ManChung Yue, WingKin Ma, Anthony ManCho 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. 40544058, 2017.
Teaching
The Hong Kong Polytechnic University

Operations Research Methods (UG). Spring 2020.
Imperial College London

Business Analytics (MSc). Spring 2019.

Advanced Machine Learning (MSc). Spring 2018.

Optimization and Decision Models (MSc). Fall 2017.

Machine Learning (MSc). Fall 2017.
The Chinese University of Hong Kong

Linear Algebra and Vector Calculus for Engineers (UG). Spring 2017.

Foundations of Optimization (PG). Fall 2016.

Linear Algebra and Vector Calculus (UG). Spring 2016.

Information Technology Management (MSc). Spring 2016.

Foundations of Optimization (PG). Fall 2015.

Principles of Engineering Management (MSc). Fall 2015.

Stochastic Models (UG). Spring 2015.

Discrete Mathematics for Engineers (UG). Fall 2014.

Technology, Society and Engineering Practices (UG). Spring 2014.

Operations Research I (UG). Fall 2013.
Contact
TU827 Yip Kit Chuen Building
The Hong Kong Polytechnic University
Hung Hom
Hong Kong
Email: manchung.yue@polyu.edu.hk