Shiva: Distributed Learning with a Local Touch: Improving Efficiency in Multiparty Learning, Kartoniert / Broschiert
Distributed Learning with a Local Touch: Improving Efficiency in Multiparty Learning
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Aktueller Preis: EUR 28,10
- Verlag:
- tredition, 06/2024
- Einband:
- Kartoniert / Broschiert, Paperback
- Sprache:
- Englisch
- ISBN-13:
- 9783384254221
- Artikelnummer:
- 11892056
- Umfang:
- 84 Seiten
- Gewicht:
- 157 g
- Maße:
- 234 x 155 mm
- Stärke:
- 7 mm
- Erscheinungstermin:
- 8.6.2024
- Hinweis
-
Achtung: Artikel ist nicht in deutscher Sprache!
Klappentext
Multiparty learning as an emerging topic, many of the related frameworks and ap-plications are proposed. In this section, we explore the extent of these frameworks and technologies.Yang et al. 72 provide a comprehensive survey of existing works on a secure fed-erated learning framework. Bonawitz et al. 8 build a scalable production system for Federated Learning in the domain of mobile devices. Kone n`yetal. 30 propose ways to reduce communication costs in federated learning. Nishio and Yonetani44 propose a new Federated Learning protocol, FedCS, which can actively manage computing workers based on their resource conditions. Zhao et al. 75 notice that conventional federated learning fails on learning non-IID data and propose a strategy to improve training on non-IID data by creating a small subset of data which is globally shared between all the edge devices. Smith et al. 63 propose fed-erated multi-task learning, which is a novel systems-aware optimization method, MOCHA.
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Shiva
Distributed Learning with a Local Touch: Improving Efficiency in Multiparty Learning
Aktueller Preis: EUR 28,10