Advances and Open Problems in Federated Learning
by Peter KairouzRachel CummingsRafael G. L. D'OliveiraHubert EichnerSalim El RouayhebDavid EvansJosh GardnerZachary GarrettAdrià GascónBadih GhaziPhillip B. GibbonsH. Brendan McMahanMarco GruteserZaid HarchaouiChaoyang HeLie HeZhouyuan HuoBen HutchinsonJustin HsuMartin JaggiTara JavidiGauri JoshiBrendan AventMikhail KhodakJakub KonecnýAleksandra KorolovaFarinaz KoushanfarSanmi KoyejoTancrède LepointYang LiuPrateek MittalMehryar MohriRichard NockAurélien BelletAyfer ÖzgürRasmus PaghHang QiDaniel RamageRamesh RaskarMariana RaykovaDawn SongWeikang SongSebastian U. StichZiteng SunMehdi BennisAnanda Theertha SureshFlorian TramèrPraneeth VepakommaJianyu WangLi XiongZheng XuQiang YangFelix X. YuHan YuSen ZhaoArjun Nitin BhagojiKallista BonawitZachary CharlesGraham Cormode
Format: Paperback
ISBN13: 9781680837889
Paperback|9781680837889
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Overview
The term Federated Learning was coined as recently as 2016 to describe a machine learning setting where multiple entities collaborate in solving a machine learning problem, under the coordination of a central server or service provider. Each client's raw data is stored locally and not exchanged or transferred; instead, focused updates intended for immediate aggregation are used to achieve the learning objective.Since then, the topic has gathered much interest across many different disciplines and the realization that solving many of these interdisciplinary problems likely requires not just machine learning but techniques from distributed optimization, cryptography, security, differential privacy, fairness, compressed sensing, systems, information theory, statistics, and more.This monograph has contributions from leading experts across the disciplines, who describe the latest state-of-the art from their perspective. These contributions have been carefully curated into a comprehensive treatment that enables the reader to understand the work that has been done and get pointers to where effort is required to solve many of the problems before Federated Learning can become a reality in practical systems.Researchers working in the area of distributed systems will find this monograph an enlightening read that may inspire them to work on the many challenging issues that are outlined. This monograph will get the reader up to speed quickly and easily on what is likely to become an increasingly important topic: Federated Learning.
| ISBN-13 | 9781680837889 |
|---|---|
| ISBN-10 | 1680837885 |
| Weight | 0.76 Pounds |
| Dimensions | 6.14 x 0.48 x 9.21 In |
| List Price | $99.00 |
| Format | Paperback |
|---|---|
| Language | English |
| Pages | 224 pages |
| Publisher | Now Publishers |
| Published On | 2021-06-23 |
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