Advanced Topics in Machine Learning - Continual Learning or Probabilistic deep learning (2022)

Description:
The Advanced Topics in Machine Learning course covers one or more selected topics of recent advances in machine learning. In particular, this year the course cover continual learning. 

Continual Learning (CL), also referred to as Lifelong or Incremental Learning, studies the problem of learning from a stream of data from changing domains, each connected to a different learning task. The objective of CL is to quickly adapt to new situations or tasks by exploiting previously acquired knowledge, while protecting previous learning from being erased. 

Teaching methods will mainly be lectures. 

Evaluation form: Hand in a short article (one page) to discuss the course content may potentially help solve the problems in the students' PhD projects.

Prerequisites:
Machine learning basics.

Organizer: Bin Yang/Miao Zhang

Lecturers: Bing Liu & Zixuan Ke, University of Illinois at Chicago (UIC)

ECTS: 2.0

Time: 15.00 to 19.00, 14 June 2022.  15.00 to 19.00, 16 June 2022. 

Place: Online 

Number of seats: 50

Deadline: 24 May

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.