28 citations · 96 across the 21 of their papers we have counts for
3 papers · 1 filter
Localized Adversarial Domain Generalization
Wei Zhu, Le Lu, Jing Xiao +3
Deep learning methods can struggle to handle domain shifts not seen in training data, which can cause them to not generalize well to unseen domains. This has led to research attent…
A Simple Hash-Based Early Exiting Approach For Language Understanding and Generation
Tianxiang Sun, Xiangyang Liu, Wei Zhu +7
Early exiting allows instances to exit at different layers according to the estimation of difficulty. Previous works usually adopt heuristic metrics such as the entropy of internal…
Structure-preserving GANs
Jeremiah Birrell, Markos A. Katsoulakis, Luc Rey-Bellet +1
Generative adversarial networks (GANs), a class of distribution-learning methods based on a two-player game between a generator and a discriminator, can generally be formulated as…