Книга Distributed Learning with a Local Touch: Improving Efficiency in Multiparty Learning SHIVA

Distributed Learning with a Local Touch: Improving Efficiency in Multiparty Learning

DE

Автор: SHIVA
Език: Английски език
Корици: С меки корици
Издател: tredition
Наличност: Външен склад
Изпращаме след 9-15 дни
19.44 38.02 лв
Multiparty learning as an emerging topic, many of the related frameworks and ap-plications are propo...

Информация за книгата

Автор
Език
Английски език
Корици
Книга - С меки корици
Издадена
2024
страници
84
EAN
9783384254221
Enbook ID
46097882
Издател
Теглоt
155
Размери
155 x 6 x 234

Пълно описание

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. Konecn`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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