After successful completion of the course, students are able to understand selected new concepts and methods of Bayesian signal processing and machine learning. Further outcomes are an improved ability to present complex facts and improved English language skills.

Joint effort to understand selected new concepts and methods of Bayesian signal processing and machine learning. Small teams of students present papers, write short reports, and/or simulate relevant methods using MATLAB or Python. This seminar is also addressed to Computer Science students as well as Masters students of Electrical Engineering outside the telecommunications branch.

Small teams of students attempt to understand selected new concepts and methods of Bayesian signal processing and machine learning. They study, present, and discuss relevant current papers, and they may also write short reports, and/or simulate relevant methods using MATLAB or Python.

Attendance required!

Class language is English

First seminar class: Wed., 09 March 2022, 2:45 -5:00 pm 

The seminar will be conducted online via Zoom. A link will be sent through TISS to those subscribed.

to be defined by the seminar participants

Registration during the first seminar unit (Wed, March 09, 2022, 14:45; online via Zoom)

Lecture notes for this course are available. Lecture notes and literature: see course 389.119 Parameter Estimation Methods

Working knowledge of random variables and linear algebra