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Where to Begin? On the Impact of Pre-Training and Initialization in Federated Learning


Oct 14, 2022
John Nguyen, Jianyu Wang, Kshitiz Malik, Maziar Sanjabi, Michael Rabbat

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* v2. arXiv admin note: substantial text overlap with arXiv:2206.15387 

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Where to Begin? Exploring the Impact of Pre-Training and Initialization in Federated Learning


Jun 30, 2022
John Nguyen, Kshitiz Malik, Maziar Sanjabi, Michael Rabbat

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* v1 

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Federated Learning with Partial Model Personalization


Apr 08, 2022
Krishna Pillutla, Kshitiz Malik, Abdelrahman Mohamed, Michael Rabbat, Maziar Sanjabi, Lin Xiao

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FedSynth: Gradient Compression via Synthetic Data in Federated Learning


Apr 04, 2022
Shengyuan Hu, Jack Goetz, Kshitiz Malik, Hongyuan Zhan, Zhe Liu, Yue Liu

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* 8 pages 

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Papaya: Practical, Private, and Scalable Federated Learning


Nov 08, 2021
Dzmitry Huba, John Nguyen, Kshitiz Malik, Ruiyu Zhu, Mike Rabbat, Ashkan Yousefpour, Carole-Jean Wu, Hongyuan Zhan, Pavel Ustinov, Harish Srinivas, Kaikai Wang, Anthony Shoumikhin, Jesik Min, Mani Malek

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Federated Learning with Buffered Asynchronous Aggregation


Jun 11, 2021
John Nguyen, Kshitiz Malik, Hongyuan Zhan, Ashkan Yousefpour, Michael Rabbat, Mani Malek Esmaeili, Dzmitry Huba

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Active Federated Learning


Sep 27, 2019
Jack Goetz, Kshitiz Malik, Duc Bui, Seungwhan Moon, Honglei Liu, Anuj Kumar

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Federated User Representation Learning


Sep 27, 2019
Duc Bui, Kshitiz Malik, Jack Goetz, Honglei Liu, Seungwhan Moon, Anuj Kumar, Kang G. Shin

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