2023
Smoothly Giving up: Robustness for Simple Models
AISTATS 2023poster
There is a growing need for models that are interpretable and have reduced energy/computational cost (e.g., in health care analytics and federated learning). Examples of algorithms to train such models include logistic regression and boosting. However, one challenge facing these algorithms is that t…