164 citations · 445 across the 25 of their papers we have counts for
5 papers · 1 filter
Hierarchical Memory Pool Based Edge Semi-Supervised Continual Learning Method
Xiangwei Wang, Rui Han, Chi Harold Liu
The continuous changes in the world have resulted in the performance regression of neural networks. Therefore, continual learning (CL) area gradually attracts the attention of more…
FedKNOW: Federated Continual Learning with Signature Task Knowledge Integration at Edge
Yaxin Luopan, Rui Han, Qinglong Zhang +2
Deep Neural Networks (DNNs) have been ubiquitously adopted in internet of things and are becoming an integral of our daily life. When tackling the evolving learning tasks in real w…
Causality Inspired Representation Learning for Domain Generalization
Fangrui Lv, Jian Liang, Shuang Li +4
Domain generalization (DG) is essentially an out-of-distribution problem, aiming to generalize the knowledge learned from multiple source domains to an unseen target domain. The ma…
Pareto Domain Adaptation
Fangrui Lv, Jian Liang, Kaixiong Gong +5
Domain adaptation (DA) attempts to transfer the knowledge from a labeled source domain to an unlabeled target domain that follows different distribution from the source. To achieve…
Active Learning for Domain Adaptation: An Energy-Based Approach
Binhui Xie, Longhui Yuan, Shuang Li +3
Unsupervised domain adaptation has recently emerged as an effective paradigm for generalizing deep neural networks to new target domains. However, there is still enormous potential…