HDFL: A Heterogeneity and Client Dropout-Aware Federated Learning Framework
Author:
Affiliation:
1. IBM Research - Almaden,San Jose,California,USA
2. University of Minnesota,Minneapolis,Minnesota,USA
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10171437/10171438/10171556.pdf?arnumber=10171556
Reference65 articles.
1. Robust and communication-efficient federated learning from non-iid data;sattler;IEEE Transactions on Neural Networks and Learning Systems,2019
2. Vafl: a method of vertical asynchronous federated learning;chen;ArXiv Preprint,2020
3. Asynchronous Online Federated Learning for Edge Devices with Non-IID Data
4. Agnostic federated learning;mohri;International Conference on Machine Learning,0
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