Tyler Farghly

Generalisation under gradient descent via deterministic PAC-Bayes

2022 · arXiv (Cornell University)

We establish disintegrated PAC-Bayesian generalisation bounds for models trained with gradient descent methods or continuous gradient flows. Contrary to standard practice in the PAC-Bayesian setting, our result applies to optimisation algorithms that are deterministic, without …