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Pisces: Efficient Federated Learning via Guided Asynchronous Training

Pisces: Efficient Federated Learning via Guided Asynchronous Training

18 June 2022
Zhifeng Jiang
Wei Wang
Baochun Li
Bo-wen Li
    FedML
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Papers citing "Pisces: Efficient Federated Learning via Guided Asynchronous Training"

11 / 11 papers shown
Title
Leakage-Resilient and Carbon-Neutral Aggregation Featuring the Federated
  AI-enabled Critical Infrastructure
Leakage-Resilient and Carbon-Neutral Aggregation Featuring the Federated AI-enabled Critical Infrastructure
Zehang Deng
Ruoxi Sun
Minhui Xue
Sheng Wen
S. Çamtepe
Surya Nepal
Yang Xiang
35
1
0
24 May 2024
Apodotiko: Enabling Efficient Serverless Federated Learning in
  Heterogeneous Environments
Apodotiko: Enabling Efficient Serverless Federated Learning in Heterogeneous Environments
Mohak Chadha
Alexander Jensen
Jianfeng Gu
Osama Abboud
Michael Gerndt
29
0
0
22 Apr 2024
FedASMU: Efficient Asynchronous Federated Learning with Dynamic
  Staleness-aware Model Update
FedASMU: Efficient Asynchronous Federated Learning with Dynamic Staleness-aware Model Update
Ji Liu
Juncheng Jia
Tianshi Che
Chao Huo
Jiaxiang Ren
Yang Zhou
H. Dai
Dejing Dou
24
31
0
10 Dec 2023
FedZero: Leveraging Renewable Excess Energy in Federated Learning
FedZero: Leveraging Renewable Excess Energy in Federated Learning
Philipp Wiesner
R. Khalili
Dennis Grinwald
Pratik Agrawal
L. Thamsen
O. Kao
24
14
0
24 May 2023
Dordis: Efficient Federated Learning with Dropout-Resilient Differential
  Privacy
Dordis: Efficient Federated Learning with Dropout-Resilient Differential Privacy
Zhifeng Jiang
Wei Wang
Ruichuan Chen
38
6
0
26 Sep 2022
Papaya: Practical, Private, and Scalable Federated Learning
Papaya: Practical, Private, and Scalable Federated Learning
Dzmitry Huba
John Nguyen
Kshitiz Malik
Ruiyu Zhu
Michael G. Rabbat
...
H. Srinivas
Kaikai Wang
Anthony Shoumikhin
Jesik Min
Mani Malek
FedML
107
137
0
08 Nov 2021
Asynchronous Federated Learning on Heterogeneous Devices: A Survey
Asynchronous Federated Learning on Heterogeneous Devices: A Survey
Chenhao Xu
Youyang Qu
Yong Xiang
Longxiang Gao
FedML
93
241
0
09 Sep 2021
Practical and Private (Deep) Learning without Sampling or Shuffling
Practical and Private (Deep) Learning without Sampling or Shuffling
Peter Kairouz
Brendan McMahan
Shuang Song
Om Thakkar
Abhradeep Thakurta
Zheng Xu
FedML
180
154
0
26 Feb 2021
Federated Evaluation and Tuning for On-Device Personalization: System
  Design & Applications
Federated Evaluation and Tuning for On-Device Personalization: System Design & Applications
Matthias Paulik
M. Seigel
Henry Mason
Dominic Telaar
Joris Kluivers
...
Dominic Hughes
O. Javidbakht
Fei Dong
Rehan Rishi
Stanley Hung
FedML
175
126
0
16 Feb 2021
FedAR: Activity and Resource-Aware Federated Learning Model for
  Distributed Mobile Robots
FedAR: Activity and Resource-Aware Federated Learning Model for Distributed Mobile Robots
Ahmed Imteaj
M. Amini
75
51
0
11 Jan 2021
IBM Federated Learning: an Enterprise Framework White Paper V0.1
IBM Federated Learning: an Enterprise Framework White Paper V0.1
Heiko Ludwig
Nathalie Baracaldo
Gegi Thomas
Yi Zhou
Ali Anwar
...
Sean Laguna
Mikhail Yurochkin
Mayank Agarwal
Ebube Chuba
Annie Abay
FedML
128
157
0
22 Jul 2020
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