This school is suitable for all levels, both for people without previous knowledge in Machine Learning, and those wishing to broaden their expertise in this area. It will allow the participants to get in touch with international experts in this field. Exchange of students, joint publications and joint projects will result because of this collaboration. For research students, the summer school provides a unique, high-quality, and intensive period of study. It is ideally suited for students currently pursuing, or intending to pursue, research in Machine Learning or related fields. For IT professionals who use Machine Learning will find that the summer school provides relevant knowledge and exposure to contemporary techniques. In addition, they will benefit by direct interaction with top-notch researchers and knowledge workers. Previous experience indicates that personnel from both the industry as well as national laboratories like CSIRO, DSTO benefit immensely from the school. For academics, the summer school is an excellent opportunity to help getting started in research on novel topics in Machine Learning. It provides an ideal forum for networking and discussions. Academics will also benefit from interaction with IT professionals which will lead to a deeper understanding of real life problems. Organizers, this summer school is organized by the Computer Sciences Laboratory of the Australian National University (CSL@ANU) and the Statistical Machine Learning program of the National ICT Australia (SML@NICTA), jointly with support from the Max-Planck-Institute for Biological Cybernetics in Tübingen and the Pascal Netwok. Please visit www.mlss.cc for more information about the previous summer schools. Local organizers are Li Cheng, Marcus Hutter, and Alex Smola.