3 citations · 4 across the 3 of their papers we have counts for
4 papers
Trustworthy Federated Learning: Privacy, Security, and Beyond
Chunlu Chen, Ji Liu, Haowen Tan +5
While recent years have witnessed the advancement in big data and Artificial Intelligence (AI), it is of much importance to safeguard data privacy and security. As an innovative ap…
Boosting Active Learning via Improving Test Performance
Tianyang Wang, Xingjian Li, Pengkun Yang +5
Central to active learning (AL) is what data should be selected for annotation. Existing works attempt to select highly uncertain or informative data for annotation. Nevertheless,…
Noise Stability Regularization for Improving BERT Fine-tuning
Hang Hua, Xingjian Li, Dejing Dou +2
Fine-tuning pre-trained language models such as BERT has become a common practice dominating leaderboards across various NLP tasks. Despite its recent success and wide adoption, th…
SMILE: Self-Distilled MIxup for Efficient Transfer LEarning
Xingjian Li, Haoyi Xiong, Chengzhong Xu +1
To improve the performance of deep learning, mixup has been proposed to force the neural networks favoring simple linear behaviors in-between training samples. Performing mixup for…