574 citations · 1k across the 14 of their papers we have counts for
4 papers · 1 filter
Learning Domain Adaptive Features with Unlabeled Domain Bridges
Yichen Li, Xingchao Peng
Conventional cross-domain image-to-image translation or unsupervised domain adaptation methods assume that the source domain and target domain are closely related. This neglects a…
Federated Adversarial Domain Adaptation
Xingchao Peng, Zijun Huang, Yizhe Zhu +1
Federated learning improves data privacy and efficiency in machine learning performed over networks of distributed devices, such as mobile phones, IoT and wearable devices, etc. Ye…
Class-imbalanced Domain Adaptation: An Empirical Odyssey
Shuhan Tan, Xingchao Peng, Kate Saenko
Unsupervised domain adaptation is a promising way to generalize deep models to novel domains. However, the current literature assumes that the label distribution is domain-invarian…
Domain Agnostic Learning with Disentangled Representations
Xingchao Peng, Zijun Huang, Ximeng Sun +1
Unsupervised model transfer has the potential to greatly improve the generalizability of deep models to novel domains. Yet the current literature assumes that the separation of tar…