2022
Generalization Error Bounds on Deep Learning with Markov Datasets
NeurIPS 2022accept
In this paper, we derive upper bounds on generalization errors for deep neural networks with Markov datasets. These bounds are developed based on Koltchinskii and Panchenko's approach for bounding the generalization error of combined classifiers with i.i.d. datasets. The development of new symmetriz…