Therefore, this paper proposes EdgeC3, a novel framework that can optimize the frequency of model aggregation and dynamic offloading for continuously generated ...
Abstract—Deep learning (DL) powered real-time applications usually need continuous training using data streams generated geographically.
It presents a study in which participants assigned learners to groups to investigate whether these, and more importantly, how they use learner personality and ...
Apr 12, 2023 · In this paper, our proposed Edge-Cloud Collaborative Knowledge Transfer Framework (ECCT) bridges the gap between the edge and cloud, enabling bi ...
Chen, EdgeC3: Online Management for Edge-Cloud Collaborative Continuous Learning, IEEE SECON 2023. Preliminary version appeared as a poster in ACM APNET ...
EdgeC3: Online Management for Edge-Cloud Collaborative Continuous Learning ... Robust Decentralized Online Learning against Malicious Data Generators and Dynamic ...
EdgeC3: Online Management for Edge-Cloud Collaborative Continuous Learning ... Robust Decentralized Online Learning against Malicious Data Generators and Dynamic ...
... Edge-MSL: Split Learning on the Mobile Edge via ... OnLine Learning Using Preemptible Cloud Instances ... EdgeC3: Online Management for Edge-Cloud ...
Jul 9, 2021 · This project is a collaborative effort between Carnegie Mellon University and Northeastern University. Results, including algorithm ...
Nov 18, 2023 · We further propose an end-to-end learning framework that incorporates the modular model design into an efficient model adaptation pipeline ...
Missing: EdgeC3: Management