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Knowledge sharing and model personalization are two key components in the conceptual framework of personalized federated learning (PFL).
Learning multiple layers of features from tiny images
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Joint structure feature exploration and regularization for multi-task graph classification
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Federated meta-learning with fast convergence and efficient communication
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Federated optimization in heterogeneous networks
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Federated learning with personalization layers
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Dagcn: dual attention graph convolutional networks
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Learning private neural language modeling with attentive aggregation
Shaoxiong Ji, Shirui Pan, Guodong Long, Xue Li, Jing Jiang, and Zi Huang · 2019
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Feddane: A federated newton-type method
Tian Li, Anit Kumar Sahu, Manzil Zaheer, Maziar Sanjabi, Ameet Talwalkar, and Virginia Smithy · 2019
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On the convergence of fedavg on non-iid data
Xiang Li, Kaixuan Huang, Wenhao Yang, Shusen Wang, and Zhihua Zhang · 2019
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Real-world image datasets for federated learning
Jiahuan Luo, Xueyang Wu, Yun Luo, Anbu Huang, Yunfeng Huang, Yang Liu, and Qiang Yang · 2019
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Graph wavenet for deep spatial-temporal graph modeling
Zonghan Wu, Shirui Pan, Guodong Long, Jing Jiang, and Chengqi Zhang · 2019
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Federated learning with hierarchical clustering of local updates to improve training on non-iid data
Christopher Briggs, Zhong Fan, and Peter Andras · 2020
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Graphfl: A federated learning framework for semi-supervised node classification on graphs
Binghui Wang, Ang Li, Hai Li, and Yiran Chen · 2020
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A comprehensive survey on graph neural networks
Zonghan Wu, Shirui Pan, Fengwen Chen, Guodong Long, Chengqi Zhang, and S Yu Philip · 2020
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Fine-tuning is fine in federated learning
Gary Cheng, Karan Chadha, and John Duchi · 2021
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Fedcv: A federated learning framework for diverse computer vision tasks
Chaoyang He, Alay Dilipbhai Shah, Zhenheng Tang, Di Fan1Adarshan Naiynar Sivashunmugam, Keerti Bhogaraju, Mita Shimpi, Li Shen, Xiaowen Chu, Mahdi Soltanolkotabi, and Salman Avestimehr · 2021
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Federated learning for object detection in autonomous vehicles
Deepthi Jallepalli, Navya Chennagiri Ravikumar, Poojitha Vurtur Badarinath, Shravya Uchil, and Mahima Agumbe Suresh · 2021
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Personalized federated learning with theoretical guarantees: A model-agnostic meta-learning approach
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An efficient framework for clustered federated learning
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Decentralized knowledge acquisition for mobile internet applications
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Scaffold: Stochastic controlled averaging for federated learning
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Think locally, act globally: Federated learning with local and global representations
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Advances and open problems in federated learning
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Personalized federated learning using hypernetworks
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Fedproto: Federated prototype learning over heterogeneous devices
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Federated learning for healthcare informatics
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Toward personalized federated learning
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Applications of federated learning in smart cities: recent advances, taxonomy, and open challenges
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