APPFLx: Providing Privacy-Preserving Cross-Silo Federated Learning as a Service-Reference-Cited by-同舟云学术

APPFLx: Providing Privacy-Preserving Cross-Silo Federated Learning as a Service

Published:2023-10-09 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 19th International Conference on e-Science (e-Science)
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Author:

Li Zilinghan¹,He Shilan¹,Chaturvedi Pranshu¹,Hoang Trung-Hieu²,Ryu Minseok³,Huerta E. A.¹,Kindratenko Volodymyr⁴,Fuhrman Jordan¹,Giger Maryellen¹,Chard Ryan¹,Kim Kibaek⁵,Madduri Ravi¹

Affiliation:

1. Argonne National Laboratory,Data Science and Learning Division,Lemont,IL,USA,60439

2. University of Illinois at Urbana-Champaign,Department of Electrical and Computer Engineering,Urbana,IL,USA,61801

3. School of Computing and Augmented Intelligence, Arizona State University,Tempe,AZ,USA,85281

4. University of Illinois at Urbana-Champaign,Department of Computer Science,Urbana,IL,USA,61801

5. Argonne National Laboratory,Mathematics and Computer Science Division,Lemont,IL,USA,60439

Funder

Argonne National Laboratory

U.S. Department of Energy

National Institutes of Health

National Science Foundation

University of Illinois at Urbana-Champaign

National Center for SuperComputing Applications

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10254737/10254662/10254842.pdf?arnumber=10254842

Reference18 articles.

1. funcX: A Federated Function Serving Fabric for Science

2. Globus auth: A research identity and access management platform

3. Adaptive federated optimization;reddi;ArXiv Preprint,2020

4. Measuring the effects of non-identical data distribution for federated visual classification;hsu;ArXiv Preprint,2019

5. Software as a service for data scientists

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