93 citations · 215 across the 12 of their papers we have counts for
12 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…
Combating Data Imbalances in Federated Semi-supervised Learning with Dual Regulators
Sikai Bai, Shuaicheng Li, Weiming Zhuang +7
Federated learning has become a popular method to learn from decentralized heterogeneous data. Federated semi-supervised learning (FSSL) emerges to train models from a small fracti…
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…
Chat-to-Design: AI Assisted Personalized Fashion Design
Weiming Zhuang, Chongjie Ye, Ying Xu +2
In this demo, we present Chat-to-Design, a new multimodal interaction system for personalized fashion design. Compared to classic systems that recommend apparel based on keywords,…
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…
Joint Optimization in Edge-Cloud Continuum for Federated Unsupervised Person Re-identification
Weiming Zhuang, Yonggang Wen, Shuai Zhang
Person re-identification (ReID) aims to re-identify a person from non-overlapping camera views. Since person ReID data contains sensitive personal information, researchers have ado…
Collaborative Unsupervised Visual Representation Learning from Decentralized Data
Weiming Zhuang, Xin Gan, Yonggang Wen +2
Unsupervised representation learning has achieved outstanding performances using centralized data available on the Internet. However, the increasing awareness of privacy protection…
Towards Unsupervised Domain Adaptation for Deep Face Recognition under Privacy Constraints via Federated Learning
Weiming Zhuang, Xin Gan, Yonggang Wen +3
Unsupervised domain adaptation has been widely adopted to generalize models for unlabeled data in a target domain, given labeled data in a source domain, whose data distributions d…
EasyFL: A Low-code Federated Learning Platform For Dummies
Weiming Zhuang, Xin Gan, Yonggang Wen +1
Academia and industry have developed several platforms to support the popular privacy-preserving distributed learning method -- Federated Learning (FL). However, these platforms ar…
Performance Optimization for Federated Person Re-identification via Benchmark Analysis
Weiming Zhuang, Yonggang Wen, Xuesen Zhang +5
Federated learning is a privacy-preserving machine learning technique that learns a shared model across decentralized clients. It can alleviate privacy concerns of personal re-iden…