The Federal Reserve Bank of Philadelphia is hosting a conference on Frontiers in Machine Learning and Economics: Methods and Applications on October 7-8, 2022. The goal of the conference is to bring together leading researchers across fields that work at the intersection of machine learning and the social sciences. The conference is co-sponsored by the Penn Institute for Economic Research and the Department of Economics of the University of Pennsylvania.
Examples of potential topics include (but are not limited to):
- Methodological advances in analyzing complex and high-dimensional data sets (e.g. likelihood-free Bayesian computation, benign overfitting).
- Methodological advances in natural language processing, in particular with respect to causal inference.
- Applications of state-of-the-art natural language processing or other machine learning methods in economics and the social sciences more broadly.
- Methodological advances in using machine learning for causal inference.
Confirmed Plenary speakers:
- Margaret Roberts (University of California - San Diego)
- Christian Robert (Université Paris-Dauphine and University of Warwick ), "How Approximate Are Approximate Bayesian Computation Methods?"
The submission deadline has passed. Attendance is by invitation only. Conference papers will be posted after the event.
For any questions, please contact Phil.Machine.Learning.Initiative@phil.frb.org.