Again this year, the Section for Cognitive Systems presents a PhD Summer School on Machine Learning.

Lecturers: Aki Vehtari (Aalto University), Ryota Tomioka (University of Tokyo), Mikkel N. Schmidt, Morten Mørup, Ole Winther, and Lars Kai Hansen.

Course description: Ph.D. Summer School in Machine Learning

The course consists of five days (Mon-Friday) of lectures and exercises on key topics in machine learning. The course (2.5 ects point) is passed by handing in a small report on one of the topics covered in the course. The course will cover key topics in machine learning including probabilistic multivariate modeling, Bayesian inference and convex optimization. The exercises cover both theoretical, technical programming and application aspects. It will be up to the students to decide on what aspects to focus on in the report. Specific machine learning application examples are used throughout the entire week.

Link to program

Link to website

This years course is sponsored by ITMAN and PASCAL2.