131 citations · 239 across the 8 of their papers we have counts for
8 papers
MAS: Towards Resource-Efficient Federated Multiple-Task Learning
Weiming Zhuang, Yonggang Wen, Lingjuan Lyu +1
Federated learning (FL) is an emerging distributed machine learning method that empowers in-situ model training on decentralized edge devices. However, multiple simultaneous FL tas…
Smart Multi-tenant Federated Learning
Weiming Zhuang, Yonggang Wen, Shuai Zhang
Federated learning (FL) is an emerging distributed machine learning method that empowers in-situ model training on decentralized edge devices. However, multiple simultaneous traini…
Optimizing Performance of Federated Person Re-identification: Benchmarking and Analysis
Weiming Zhuang, Xin Gan, Yonggang Wen +1
The increasingly stringent data privacy regulations limit the development of person re-identification (ReID) because person ReID training requires centralizing an enormous amount o…
Divergence-aware Federated Self-Supervised Learning
Weiming Zhuang, Yonggang Wen, Shuai Zhang
Self-supervised learning (SSL) is capable of learning remarkable representations from centrally available data. Recent works further implement federated learning with SSL to learn…
Federated Unsupervised Domain Adaptation for Face Recognition
Weiming Zhuang, Xin Gan, Yonggang Wen +3
Given labeled data in a source domain, unsupervised domain adaptation has been widely adopted to generalize models for unlabeled data in a target domain, whose data distributions a…
Characterization and Prediction of Deep Learning Workloads in Large-Scale GPU Datacenters
Qinghao Hu, Peng Sun, Shengen Yan +2
Modern GPU datacenters are critical for delivering Deep Learning (DL) models and services in both the research community and industry. When operating a datacenter, optimization of…