Advances and Open Problems in Federated Learning |
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| Author:
| Kairouz, Peter
McMahan, H. Brendan
Avent, Brendan
Bellet, Aurélien
Bennis, Mehdi
Bhagoji, Arjun Nitin
Bonawit, Kallista
Charles, Zachary
Cormode, Graham
Cummings, Rachel
D'Oliveira, Rafael G. L.
Eichner, Hubert
El Rouayheb, Salim
Evans, David
Gardner, Josh
Garrett, Zachary
Gascón, Adrià
Ghazi, Badih
Gibbons, Phillip B.
Gruteser, Marco
Harchaoui, Zaid
He, Chaoyang
He, Lie
Huo, Zhouyuan
Hutchinson, Ben
Hsu, Justin
Jaggi, Martin
Javidi, Tara
Joshi, Gauri
Khodak, Mikhail
Konecný, Jakub
Korolova, Aleksandra
Koushanfar, Farinaz
Koyejo, Sanmi
Lepoint, Tancrède
Liu, Yang
Mittal, Prateek
Mohri, Mehryar
Nock, Richard
Özgür, Ayfer
Pagh, Rasmus
Qi, Hang
Ramage, Daniel
Raskar, Ramesh
Raykova, Mariana
Song, Dawn
Song, Weikang
Stich, Sebastian U.
Sun, Ziteng
Theertha Suresh, Ananda
Tramèr, Florian
Vepakomma, Praneeth
Wang, Jianyu
Xiong, Li
Xu, Zheng
Yang, Qiang
Yu, Felix X.
Yu, Han
Zhao, Sen |
| Series title: | Foundations and Trends in Machine Learning Ser. |
| ISBN: | 978-1-68083-788-9 |
| Publication Date: | Jun 2021 |
| Publisher: | Now Publishers
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| Book Format: | Paperback |
| List Price: | USD $99.00 |
Book Description:
|
Researchers working in the area of distributed systems will find this book an enlightening read that may inspire them to work on the many challenging issues that are outlined. This book will get the reader up to speed quickly and easily on what is likely to become an increasingly important topic; Federated Learning.
Researchers working in the area of distributed systems will find this book an enlightening read that may inspire them to work on the many challenging issues that are outlined. This book will get the reader up to speed quickly and easily on what is likely to become an increasingly important topic; Federated Learning.