T-61.181 Special course in Information Science I (4 ov) (L)
ICA, Autumn 2001
This graduate course is based on the brand new book Independent Component Analysis (J. Wiley, 2001), written by A. Hyvärinen, J. Karhunen, and E. Oja from our laboratory. The central parts of the book will be covered by lectures given by Profs. J. Karhunen and E. Oja.
Place: Seminar room Y313 in the main building of HUT
ICA is one of the most exciting topics in the fields of neural computation, advanced statistics, and signal processing. The text-book as well as the lecture course will provide a comprehensive introduction to this new technique complete with the mathematical background needed to understand and utilize it. It offers a general overview of the basics of ICA, important solutions and algorithms, and in-depth coverage of new applications in vision research, brain imaging, telecommunications, and more.
You need only the basic knowledge about probability and statistics, matrix algebra, and algorithms in order to follow the course. The first lectures will be used to cover the necessary background.
Requirements for passing the course
To pass the course with 4 credits, you have to
To pass with distinction, you must solve 90 % of your exercise problems in a satisfactory way, and do excellent projects with high level reports to match.
However, there is a certain overlap between this course and some previous graduate courses on ICA and unsupervised learning. If you have passed the Special Course on unsupervised learning held last autumn by Hyvärinen and Girolami, or one of the earlier ICA courses, please contact the lecturers to agree on the credit points.
Signing up for the course
Please come to the first lecture on Monday, September 17.
Monday, 24-Sep-2001 15:56:19 EEST