Adaptive Systems Seminar

6 ECTS credits
150 h study time

Offer 1 with catalog number 4018115ENR for all students in the 2nd semester at a (E) Master - advanced level.

Semester

2nd semester

Enrollment based on exam contract

Impossible

Grading method

Grading (scale from 0 to 20)

Can retake in second session

Yes

Taught in

English

Partnership Agreement

Under agreement for exchange of courses

Faculty

Faculty of Sciences and Bioengineering Sciences

Department

Computer Science

Educational team

Bernard Manderick (course titular)

Activities and contact hours

26 contact hours Lecture
26 contact hours Seminar, Exercises or Practicals

Course Content

During this course we will watch a number of video MLSS lectures on a number of machine learning topics. MLSS stands for Machine Learning Summer School and is recurring summer school for PhD students in machine learning. The lectures are giving by top experts on the particular topic.

Course material

Digital course material (Required) : http://como.vub.ac.be/ under the heading Teaching
Digital course material (Required) : http://www.unifr.ch/econophysics/minority/ for more information on that game and its applications for multi-agent systems and distributed resource allocation
Digital course material (Required) : A selection of state of the art research papers on machine learning and complex dynamical systems

Additional info

The lastest information can be found on the webpage of this course at https://ai.vub.ac.be/courses/

Learning Outcomes

General competencies

Overall, to acquire the necessary skills to understand and to make a synthesis of the state of the art topics in machine learning and complex dynamical systems.
Knowledge and insight: After successful completion, the student should have knowledge and insight in the domain of machine learning and complex dynamical systems which allows her or him to provide an original contribution to the domain.
The use of knowledge and insight: The student is able to combine the ideas discussed in the course to tackle a new problem in an interesting way.

Judgement ability: The student can make an independent judgement of papers in these scientific domains.

Communication: The student is able to present the papers reviewed during the course to fellow students and to formulate his own opinion concerning the content.

Skills: The student can search for, collect, read and synthesize papers in this area of research.

Grading

The final grade is composed based on the following categories:
LEC Teamwork determines 50% of the final mark.
PRAC Paper determines 50% of the final mark.

Within the LEC Teamwork category, the following assignments need to be completed:

Class participation with a relative weight of 1 which comprises 50% of the final mark.

Within the PRAC Paper category, the following assignments need to be completed:

Synthesis paper with a relative weight of 1 which comprises 50% of the final mark.

Additional info regarding evaluation

Permanent evaluation based on

1. Presence during the video lectures
1.1 At the beginning of each class students have to sign an attendance list.
1.2 If you cannot be present for some reason then you have to send an email beforehand to bernard.manderick@vub.be.

2. Activity during the class

3. Extra marks can be obtained by presenting own work related to the topics discussed during the course.

Allowed unsatisfactory mark

The supplementary Teaching and Examination Regulations of your faculty stipulate whether an allowed unsatisfactory mark for this programme unit is permitted.

Academic context