I will continue teaching the postgraduate level course “SEEM5350: Numerical Optimization” in the Spring semester 2017 (Jan-Apr 2017). Note that the course has a new course code.
Check out the course website [course website]. The course will cover optimization algorithms such as gradient
proximal gradient method, accelerated first-order method, operator-splitting and alternating direction methods, (block) coordinate descent method, randomized first-order method etc. Applications of
algorithms in big data analytics, machine learning, statistics and image processing etc will also be discussed. Feel free to send me an email if you are interested in learning
more about this course.
I am organizing a group meeting on Friday morning every week in the Spring semester of 2016. We study various research topics on convex optimization, online optimization, stochastic optimization and their applications in big data
analytics, machine learning, statistical learning, image processing, signal processing etc.
Papers will be presented by my students and visitors randomly. Everyone is welcome to join our meeting if you find the topics interesting. Send me an email if you are interested in joining the meeting.
I work on theory and algorithm of optimization and its various applications. Currently, I focus on theory and algorithms for structured convex and nonconvex optimization, first-order methods, stochastic optimization, polynomial and tensor optimization,
and applications arising from big data analytics, machine learning, statistics, image processing, signal processing, bioinformatics etc.
Department of Systems Engineering and Engineering Management
Room 508, William M.W. Mong Engineering Building
The Chinese University of Hong Kong
Tel: (852) 3943-8240
Fax: (852) 2603-5505
Email: sqma at se.cuhk.edu.hk