John Langford (Yahoo Research)
Title: The Reduction Approach to Machine Learning
Time: October 12-13, 2006
Location: Room B222, Exactum, Department of Computer Science, University of Helsinki, Gustaf Hällströmin katu 2b
Schedule: Lectures 12-15.
Registration is voluntary. Please, inform
firstname.lastname@example.org if you are planning to participate.
Grading: If you want to get credits (2-6 credit units), choose one of the following homework projects.
The reduction approach to machine learning solves learning problems by reducing them to known learning problems and applying known algorithms. I will discuss this approach in sufficient detail so that anyone may use (and improve) it in two 3 hour lectures (with breaks, naturally).
John Langford's page Machine Learning Reductions contains also the slides for this course.
On the first day, I'll cover the basics:
On the second day, I'll cover more advanced topics:
Passing the course: If you want to get credits (2-6 credit units), choose one of the following homework projects.
For more details on the project, credits, and other practical issues, please contact Matti Kääriäinen (email@example.com).
|Links: John Langford's home page|