As the development of machine learning algorithms advances rapidly, they play larger and larger roles for our societies. People both in- and outside the technical domain are rightfully concerned about the fairness of such algorithms:How can we explain, justify and assign accountability for automated decisions made by complex ML models? How do deep learning algorithms propagate existing bias and stereotypes? How can we define and measure algorithmic fairness?While those questions certainly aren't engineering problems alone, this year's summer school will consider them from a technical perspective.
The course consists of five days (Mon-Friday) of lectures and exercises. The lectures will cover theoretical aspects such as explainability of deep learning models, causal reasoning and fairness metrics. Technical aspects, programming and application of the developed concepts will be explored in tutorials and exercises. The course (2.5 ECTS points) is passed by handing in a small report on one of the topics covered in the course and/or by presenting relevant work at a poster session.
Technical University of Denmark, room TBA.
Every day August August 26-30, 2019, exact starting and end times TBA.
Speakers TBA, the following list of confirmed speakers will be updated with invited speakers and staff at the Section for Cognitive Systems throughout spring:
General understanding of machine learning, statistical modeling, mathematics and computer science. Programming experience, ideally in Python. For the course you are required to bring your own laptop computer with a Python installation.
As we anticipate more applicants than we have space for applicants will be selected based on their curriculum vitae (CV). To register please send an email to Wanja Andersenwaan@dtu.dk with your CV (maximum 2 pages). The CV has to be received no later than 14th of June. We will notify applicants regarding acceptance to the summer school 21th of June.
For academics (masters and PhD students) there is no registration fee for the course. For all other participants a course fee of DKK 8250 will be charged. Participants are to cover all other costs such as food, accommodation, and travel expenses.
2018 version of 02901 Advanced Topics in Machine Learning
2017 version of 02901 Advanced Topics in Machine Learning
2016 version of 02901 Advanced Topics in Machine Learning
2015 version of 02901 Advanced Topics in Machine Learning
2014 version of 02901 Advanced Topics in Machine Learning
For further information, please contact: