Joint Focal Loss and Dominant Gradient Correction for Gradient Conflict in Federated Learning
Author:
Affiliation:
1. Hohai University,School of Computer and Information,Nanjing,China
2. Hohai University,Key Laboratory of Water Big Data Technology of Ministry of Water Resources,Nanjing,China
3. Temple University,Center for Networked Computing,Philadelphia,USA
Funder
Research and Development
Hohai University
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10298257/10298281/10298316.pdf?arnumber=10298316
Reference27 articles.
1. Adaptive federated optimization;sashank;9th International Conference on Learning Representations,2021
2. Slowmo: improving communication-efficient distributed SGD with slow momentum;wang;8th International Conference on Learning Representations,2021
3. Communication-efficient learning of deep networks from decentralized data;mcmahan;Proceedings of the 20th International Conference on Artificial Intelligence and Statistics,2017
4. Inverse Distance Aggregation for Federated Learning with Non-IID Data
5. When Decentralized Optimization Meets Federated Learning
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