Kursanalys: Statistical Methods in Applied Computer Science, statmet09
For the 2008 analysis, see 'andra omgångar'
Statistical Methods in Applied Computer Science, 2D1447 4p, 6 ECTS(hp).
Course given in Spring 2008
Instructor: Stefan Arnborg
Lectures: 18 hours
Registered students: 18 Master's students(DD2447)+4 doctoral student(FDD3342)
Lecture Notes: Statistical Methods
in Applied Computer Science
Course has one examined moment, labelled as Homework
Throughput: 100% (14 Master's students had passed to grade C after last lecture, by doing 6 weekly homeworks). One student achieved higher grade B by doing one Master's tests, and three students obtained grade A after two Master's tests or one project.
This course summarizes statistical and probabilistic methods used in applied Computer Science - statistical aspects of Data Mining, Knowledge Discovery, Machine learning and Information Fusion with a Bayesian outlook.
After successfully taking this course, you will be able to:
-motivate the use of uncertainty management and statistical methodology in computer science applications, as well as the main methods in use,
-account for algorithms used in the area and use the standard tools,
-critically evaluate the applicability of these methods in new contexts, and design new applications of uncertainty management,
-follow research and development in the area.
Changes made in 2009:
No change, but some extra rehearsal was introduced. Lectures and material on Gammerman/Vovk inference and recommender systems was popular.
I liked giving the course, few problems except that I think people did not like to see how nuiscance parameters are eliminated by integration in joint inferences of variance and mean for gaussian mixture modelling. I will try to skip that next time.
OK. individual examination is however somewhat time-consuming
Seemed to work fine. I will do some refinements in the compendium, but just now I have not found new stuff to throw in. Maybe oracle property in feature selection, a hot but difficult topic in high-throughput bioinformatics.