ICML 2010 Tutorial on Privacy and Machine Learning

Stan Matwin, University of Ottawa, Canada


This tutorial will give a bird's eyes view of the area of privacy as it pertains to Machine Learning. The area is sometimes known as Privacy-preserving Data Mining (PPDM). This is an interesting and highly significant topic for the community because privacy is one of the main ethical/societal concerns surrounding IT in general and Machine Learning in particular. Many believe that there is moral obligation for at least some in the community to work in this area to propose privacy-protecting solutions. Moreover, there is an emerging body of work in Privacy-preserving Data Mining that needs to be presented to the community. Finally, the area of privacy is a fertile area of work/research for people looking for theses topics, new research directions, etc.

Who should attend

Since this is an important topic for the community, the tutorial will be of interest to graduate students and researchers. The tutorial has no specific prerequisites for the target audience.



Slides are availablel here (pdf, two per page)


Stan Matwin is a professor of Computer Science at the University of Ottawa, active in Machine Learning research and teaching since many years. Privacy and PPDM is one of his active research areas.