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Applied Federated Learning: Architectural Design for Robust and
  Efficient Learning in Privacy Aware Settings

Applied Federated Learning: Architectural Design for Robust and Efficient Learning in Privacy Aware Settings

2 June 2022
B. Stojković
Jonathan Woodbridge
Zhihan Fang
Jerry Cai
Andrey Petrov
Sathya Iyer
Daoyu Huang
Patrick Yau
Arvind Sastha Kumar
Hitesh Jawa
Anamita Guha
    FedML
ArXivPDFHTML

Papers citing "Applied Federated Learning: Architectural Design for Robust and Efficient Learning in Privacy Aware Settings"

4 / 4 papers shown
Title
FL-APU: A Software Architecture to Ease Practical Implementation of Cross-Silo Federated Learning
FL-APU: A Software Architecture to Ease Practical Implementation of Cross-Silo Federated Learning
F. Stricker
J. A. Peregrina
D. Bermbach
C. Zirpins
FedML
78
0
0
31 Jan 2025
Efficient and Light-Weight Federated Learning via Asynchronous
  Distributed Dropout
Efficient and Light-Weight Federated Learning via Asynchronous Distributed Dropout
Chen Dun
Mirian Hipolito Garcia
C. Jermaine
Dimitrios Dimitriadis
Anastasios Kyrillidis
66
20
0
28 Oct 2022
Decision Models for Selecting Federated Learning Architecture Patterns
Decision Models for Selecting Federated Learning Architecture Patterns
Sin Kit Lo
Qinghua Lu
Hye-Young Paik
Liming Zhu
AI4CE
FedML
37
0
0
28 Apr 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
113
137
0
08 Nov 2021
1