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portada Decentralized Optimization in Networks: Algorithmic Efficiency and Privacy Preservation
Type
Physical Book
Publisher
Author
Language
English
Pages
276
Format
Paperback
ISBN13
9780443333378

Decentralized Optimization in Networks: Algorithmic Efficiency and Privacy Preservation

Qingguo Lü Ms; Xiaofeng Liao Phd; Huaqing Li Phd; Shaojiang Deng Phd; Yantao Li Phd; Keke Zhang Ms (Author) · Morgan Kaufmann Publishers · Paperback

Decentralized Optimization in Networks: Algorithmic Efficiency and Privacy Preservation - Qingguo Lü Ms; Xiaofeng Liao Phd; Huaqing Li Phd; Shaojiang Deng Phd; Yantao Li Phd; Keke Zhang Ms

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Synopsis "Decentralized Optimization in Networks: Algorithmic Efficiency and Privacy Preservation"

Decentralized Optimization in Networks: Algorithmic Efficiency and Privacy Preservation provides the reader with theoretical foundations, practical guidance, and solutions to decentralized optimization problems. The book demonstrates the application of decentralized optimization algorithms to enhance communication and computational efficiency, solve large-scale datasets, maintain privacy preservation, and address challenges in complex decentralized networks. The book covers key topics such as event-triggered communication, random link failures, zeroth-order gradients, variance-reduction, Polyak's projection, stochastic gradient, random sleep, and differential privacy. It also includes simulations and practical examples to illustrate the algorithms' effectiveness and applicability in real-world scenarios.

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The binding of this edition is Paperback.

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