113 citations · 282 across the 27 of their papers we have counts for
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cs.LG2020★ 3 cited
Weight-Covariance Alignment for Adversarially Robust Neural Networks
Panagiotis Eustratiadis, Henry Gouk, Da Li +1
Stochastic Neural Networks (SNNs) that inject noise into their hidden layers have recently been shown to achieve strong robustness against adversarial attacks. However, existing SN…
cs.CV2020★ 2 cited
Sequential Learning for Domain Generalization
Da Li, Yongxin Yang, Yi-Zhe Song +1
In this paper we propose a sequential learning framework for Domain Generalization (DG), the problem of training a model that is robust to domain shift by design. Various DG approa…
cs.CV2020★ 6 cited
Online Meta-Learning for Multi-Source and Semi-Supervised Domain Adaptation
Da Li, Timothy Hospedales
Domain adaptation (DA) is the topical problem of adapting models from labelled source datasets so that they perform well on target datasets where only unlabelled or partially label…