no code implementations • 28 Sep 2020 • Elliot Creager, Joern-Henrik Jacobsen, Richard Zemel
Developing learning approaches that are not overly sensitive to the training distribution is central to research on domain- or out-of-distribution generalization, robust optimization and fairness.
4 code implementations • 2 Mar 2020 • David Krueger, Ethan Caballero, Joern-Henrik Jacobsen, Amy Zhang, Jonathan Binas, Dinghuai Zhang, Remi Le Priol, Aaron Courville
Distributional shift is one of the major obstacles when transferring machine learning prediction systems from the lab to the real world.