Events

12/05/
2022
Monday
4:00pm
University of Chicago
Title: Testing the stability of a black-box algorithm

Many results on generalization and distribution-free inference depend on the stability of a regression algorithm, which is often defined as the property that predictions on a new test point are not substantially altered by removing a single point at random from the training set.

12/12/
2022
Monday
4:00pm
New York University
Title: TBA
12/19/
2022
Monday
4:00pm
University of Pennsylvania
Title: Efficient derivative-free Bayesian inference for large-scale inverse problems

We consider Bayesian inference for large-scale inverse problems, where computational challenges arise from the need for the repeated evaluations of an expensive forward model, which is often given as a black box or is impractical to differentiate.