3 citations · 4 across the 3 of their papers we have counts for
3 papers
cs.LG2024
Denoising-Aware Contrastive Learning for Noisy Time Series
Shuang Zhou, Daochen Zha, Xiao Shen +3
Time series self-supervised learning (SSL) aims to exploit unlabeled data for pre-training to mitigate the reliance on labels. Despite the great success in recent years, there is l…
cs.LG2020★ 1 cited
Against Adversarial Learning: Naturally Distinguish Known and Unknown in Open Set Domain Adaptation
Sitong Mao, Xiao Shen, Fu-lai Chung
Open set domain adaptation refers to the scenario that the target domain contains categories that do not exist in the source domain. It is a more common situation in the reality co…
cs.LG2019★ 3 cited
Graph Transfer Learning via Adversarial Domain Adaptation with Graph Convolution
Quanyu Dai, Xiao-Ming Wu, Jiaren Xiao +2
This paper studies the problem of cross-network node classification to overcome the insufficiency of labeled data in a single network. It aims to leverage the label information in…