Federated Class-Incremental Learning
Author:
Affiliation:
1. Shenyang Institute of Automation, Chinese Academy of Sciences,State Key Laboratory of Robotics
2. Northwestern University
3. University of Technology Sydney,DeSI Lab, AAII
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9878378/9878366/09878590.pdf?arnumber=9878590
Reference58 articles.
1. Distributed Federated Learning for Ultra-Reliable Low-Latency Vehicular Communications
2. On the convergence of federated optimization in heterogeneous networks;sahu;ar Xiv preprint,2018
3. Diot: A crowdsourced self-learning approach for detecting compromised iot devices;nguyen;ArXiv Preprint,2018
4. Federated learning of deep networks using model averaging;mcmahan;ArXiv Preprint,2016
5. A novel attribute re-construction attack in federated learning;lyu;ar Xiv preprint,2021
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