Association analysis is an important technology in data mining, and has been widely used in many application areas. However, associations in data can be spurious and they do not indicate causal-effect relationships that are ultimate goals for many scientific explorations and social studies. While the techniques for association discovery become mature, the problem for identifying non-spurious associations becomes prominent. In this talk, I will discuss some current methods for causal relationship discovery and our research work in this direction.
About the Speaker
Prof. Jiuyong Li is a Professor and an Associate Head of School at the School of Information Technology and Mathematical Sciences of University of South Australia. He leads the Data Analytics Group in the School. His main research interests are in data mining, bioinformatics, and data privacy. He has led five Australian Research Council Discovery projects and leads a Data to Decision CRC project. He has published more than 100 papers, mostly in leading journals and conferences in the areas. His software tools have been used in several real world projects. He has been a chair (or a PC chair) of multiple Australasian data mining and artificial intelligence conferences and international causal discovery workshops. He has received senior visiting fellowships from Nokia Foundation, the Australian Academy of Science, and Japan Society of Promotion of Science.
About the seminar series
This seminar series exists to bring together South Australians with a common interest in machine learning so as to encourage new collaboration and partnerships. This is the 5th talk for 2016. Expect more great speakers and events in the future.