294 citations · 573 across the 32 of their papers we have counts for
5 papers · 1 filter
Latent Dirichlet Allocation Model Training with Differential Privacy
Fangyuan Zhao, Xuebin Ren, Shusen Yang +3
Latent Dirichlet Allocation (LDA) is a popular topic modeling technique for hidden semantic discovery of text data and serves as a fundamental tool for text analysis in various app…
DPCrowd: Privacy-preserving and Communication-efficient Decentralized Statistical Estimation for Real-time Crowd-sourced Data
Xuebin Ren, Chia-Mu Yu, Wei Yu +3
In Internet of Things (IoT) driven smart-world systems, real-time crowd-sourced databases from multiple distributed servers can be aggregated to extract dynamic statistics from a l…
CDC: Classification Driven Compression for Bandwidth Efficient Edge-Cloud Collaborative Deep Learning
Yuanrui Dong, Peng Zhao, Hanqiao Yu +2
The emerging edge-cloud collaborative Deep Learning (DL) paradigm aims at improving the performance of practical DL implementations in terms of cloud bandwidth consumption, respons…
OL4EL: Online Learning for Edge-cloud Collaborative Learning on Heterogeneous Edges with Resource Constraints
Qing Han, Shusen Yang, Xuebin Ren +3
Distributed machine learning (ML) at network edge is a promising paradigm that can preserve both network bandwidth and privacy of data providers. However, heterogeneous and limited…
SurveilEdge: Real-time Video Query based on Collaborative Cloud-Edge Deep Learning
Shibo Wang, Shusen Yang, Cong Zhao
The real-time query of massive surveillance video data plays a fundamental role in various smart urban applications such as public safety and intelligent transportation. Traditiona…