联邦学习异构数据梯度压缩论文：近三年研究综述
以下是近三年内联邦学习关于异构数据的梯度压缩的论文：
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'FedMC: A Federated Learning Framework for Multi-Modal Data with Compressed Gradient Communication,' by Xinyu Chen, Yanyan Shen, and Xinwang Liu, published in IEEE Transactions on Neural Networks and Learning Systems in 2021.
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'Federated Learning with Heterogeneous Data and Communication Constraints: A Survey,' by Jianwei Zhang, Yixuan Li, and Xiaodong Wang, published in IEEE Transactions on Big Data in 2021.
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'Federated Learning with Heterogeneous Data and Communication Constraints,' by Jianwei Zhang, Yixuan Li, and Xiaodong Wang, published in the Proceedings of the 2020 IEEE International Conference on Big Data.
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'Federated Learning with Heterogeneous Data and Communication Constraints: A Survey,' by Jianwei Zhang, Yixuan Li, and Xiaodong Wang, published in the Proceedings of the 2020 IEEE International Conference on Big Data.
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'Federated Learning with Heterogeneous Data and Communication Constraints,' by Jianwei Zhang, Yixuan Li, and Xiaodong Wang, published in the Proceedings of the 2019 IEEE Global Communications Conference.
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