August 13-17, 2012, DTU Informatics, Cognitive Systems
Lecturers: Aki Vehtari (Aalto University), Ryota Tomioka (University of Tokyo), Mikkel N. Schmidt, Morten Mørup, Ole Winther, and Lars Kai Hansen.
Place: Technical University of Denmark, bld. 421 auditorium 73
Hours: 09.30 – 17.00
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.
Click here for a full programme.
Mikkel N. Schmidt
Introduction to Bayesian inference
Bayesian predictive methods for model assessment, selection and comparison
Extra Lecture slides (CV and WAIC)
Introduction to Convex Optimization
Lars Kai Hansen
Learning from small samples in high dimensions
Lecture slides and exercise material
Bayesian Models for Complex Networks
To register please send an e-mail to Marian Solrun Adler
For practical information regarding transportation and accommodation click here.
For further information, please contact:
Associate Professor, Ph.D. Morten Mørup,
Phone: +45 45253900
Associate Professor, Ph.D. Ole Winther,
Phone: +45 45253895
Professor, Ph.D. Lars Kai Hansen,
Phone: +45 45253889
DTU Informatics, Section for Cognitive Systems, Building 321, 1. floor.
This years course is sponsored by ITMAN and PASCAL2.
Other relevant PhD summer schools in Copenhagen, August 2012:
Summer School on Massive Data Mining (August 8-10)
Domain Adaptation in Image Analysis (August 20-24)
Computational Data Analysis (August 27-31)