42 citations · 78 across the 12 of their papers we have counts for
4 papers · 1 filter
Learning to Learn Domain-invariant Parameters for Domain Generalization
Feng Hou, Yao Zhang, Yang Liu +6
Due to domain shift, deep neural networks (DNNs) usually fail to generalize well on unknown test data in practice. Domain generalization (DG) aims to overcome this issue by capturi…
Self-Supervised Graph Neural Network for Multi-Source Domain Adaptation
Jin Yuan, Feng Hou, Yangzhou Du +4
Domain adaptation (DA) tries to tackle the scenarios when the test data does not fully follow the same distribution of the training data, and multi-source domain adaptation (MSDA)…
Disentangled Neural Architecture Search
Xinyue Zheng, Peng Wang, Qigang Wang +1
Neural architecture search has shown its great potential in various areas recently. However, existing methods rely heavily on a black-box controller to search architectures, which…
Efficient Automatic Meta Optimization Search for Few-Shot Learning
Xinyue Zheng, Peng Wang, Qigang Wang +2
Previous works on meta-learning either relied on elaborately hand-designed network structures or adopted specialized learning rules to a particular domain. We propose a universal f…