Statistical decisions are often given meaning in the context of other decisions, particularly when there are scarce resources to be shared. Managing such sharing is one of the classical goals of microeconomics, and it is given new relevance in the modern setting of large, human-focused datasets, and in data-analytic contexts such as classifiers and recommendation systems.
Michael Jordan will discuss several recent projects that aim to explore the interface between machine learning and microeconomics, including the study of exploration-exploitation trade-offs for bandit learning algorithms that compete over a scarce resource, leader/follower dynamics in strategic classification, and the robust learning of optimal auctions.
- Prof. Michael I. Jordan, Pehong Chen Distinguished Professor at the Department of Electrical Engineering and Computer Sciences and the Department of Statistics of the University of California, Berkeley
- Prof. Dr. Gitta Kutyniok, Bavarian AI Chair for Mathematical Foundations of Artificial Intelligence, LMU
The event will be streamed in English. Prior registration by email is required. For further information, see the CAS website.
The Center for Advanced Studies at LMU provides a forum for scientific exchange and discussion that bridges the divide between the established disciplines. Its activities are designed to promote all forms of collaborative research and to stimulate interdisciplinary communication within the University. In addition, it facilitates the integration of visiting scholars and scientists into the academic life of the University.