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Destinazione, tempi e costiDa: California Books, Miami, FL, U.S.A.
Condizione: New. Codice articolo I-9781680837889
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Da: PBShop.store US, Wood Dale, IL, U.S.A.
PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Codice articolo L0-9781680837889
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Da: PBShop.store UK, Fairford, GLOS, Regno Unito
PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Codice articolo L0-9781680837889
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Da: Russell Books, Victoria, BC, Canada
Paperback. Condizione: New. Special order direct from the distributor. Codice articolo ING9781680837889
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Da: Chiron Media, Wallingford, Regno Unito
PF. Condizione: New. Codice articolo 6666-IUK-9781680837889
Quantità: 10 disponibili
Da: Ria Christie Collections, Uxbridge, Regno Unito
Condizione: New. In. Codice articolo ria9781680837889_new
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Da: THE SAINT BOOKSTORE, Southport, Regno Unito
Paperback / softback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 185. Codice articolo C9781680837889
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Da: Revaluation Books, Exeter, Regno Unito
Paperback. Condizione: Brand New. 226 pages. 9.21x6.14x0.48 inches. In Stock. Codice articolo x-1680837885
Quantità: 2 disponibili
Da: Books Puddle, New York, NY, U.S.A.
Condizione: New. pp. 226. Codice articolo 26388204700
Quantità: 4 disponibili
Da: AHA-BUCH GmbH, Einbeck, Germania
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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. Codice articolo 9781680837889
Quantità: 1 disponibili