2022
Generalization Bounds for Gradient Methods via Discrete and Continuous Prior
NeurIPS 2022accept
Proving algorithm-dependent generalization error bounds for gradient-type optimization methods has attracted significant attention recently in learning theory. However, most existing trajectory-based analyses require either restrictive assumptions on the learning rate (e.g., fast decreasing learning…