Learning sparse generalized linear models with binary outcomes via iterative hard thresholding

Namiko Matsumoto, Arya Mazumdar

In statistics, generalized linear models (GLMs) are widely used for modeling data and can expressively capture potential nonlinear dependence of the model's outcomes on its covaria…