The course will start from the basics of Bayesian learning, i.e., Bayes' theorem and it will focus on fundamenal concepts around the Baysiann treatment of the classical regression task. The power of the evidence function will be demonstrated, mainly via concepts and physical reasoning, and its reltaion to Occam's razor rule for adressing overfitting will be demonstrated. Then, the concept of latent variables and the EM algorith will be reviewed, with applications to regression, classification and clustering. Finally, extentions to the variational EM algortihm will be discussed with applications to regression and mixture modelling.
Organizer: Sergios Theodoridis
Lecturers: Sergios Theodoridis
ECTS: 1
Time: 8 May - 12 May 2023, all days 9.00 - 12.00
Place: FRB 7B2-104 all days
Zip code:
City:
Number of seats: 20
Deadline: 17 April 2023
Important information concerning PhD courses:
We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3.000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.
- Teacher: Sergios Theodoridis