activity
20192022
most citedLDP-IDS: Local Differential Privacy for Infinite Data Streams

85 citations · 116 across the 4 of their papers we have counts for

collaborators

5 papers

cs.DB202285 cited

LDP-IDS: Local Differential Privacy for Infinite Data Streams

Xuebin Ren, Liang Shi, Weiren Yu +3

Streaming data collection is essential to real-time data analytics in various IoTs and mobile device-based systems, which, however, may expose end users' privacy. Local differentia…

cs.DC20224 cited

ACE: Towards Application-Centric Edge-Cloud Collaborative Intelligence

Luhui Wang, Cong Zhao, Shusen Yang +2

Intelligent applications based on machine learning are impacting many parts of our lives. They are required to operate under rigorous practical constraints in terms of service late…

cs.DC2020

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…

cs.DC2020

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…

cs.LG201927 cited

Asynchronous Federated Learning with Differential Privacy for Edge Intelligence

Yanan Li, Shusen Yang, Xuebin Ren +1

Federated learning has been showing as a promising approach in paving the last mile of artificial intelligence, due to its great potential of solving the data isolation problem in…