COMP9418 Advanced Topics in Statistical Machine Learning  
This course provides an in-depth study of statistical machine learning approaches. The
focus will be on methods for learning and inference in structured probabilistic
models, with a healthy balance of theory and practice. It is aimed
at postgraduate students and advanced undergraduates who are willing to be go
beyond basic understanding of machine learning. The course provides fundamental support for
those willing to intensify their knowledge in the area of big data
analytics.  
It will cover topics on exact and approximate inference in probabilistic graphical
models; learning in structured latent variable models; posterior inference in non-parametric models
based on Gaussian processes; and relational learning.