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Padua Thesis and Dissertation Archive
Bachelor thesis
Full-Text: https://thesis.unipd.it/bitstream/20.500.12608/27005/1/tesi_Bastianello_Nicola.pdf
Data sources: Padua Thesis and Dissertation Archive
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Distributed Convex Optimisation using the Alternating Direction Method of Multipliers (ADMM) in Lossy Scenarios

descriptionPublicationkeyboard_double_arrow_right Bachelor thesis Italy English
Authors: Bastianello, Nicola#idabnull;

handle: 20.500.12608/27005

Distributed Convex Optimisation using the Alternating Direction Method of Multipliers (ADMM) in Lossy Scenarios

Abstract

The Alternating Direction Method of Multipliers (ADMM) is an extensively studied algorithm suitable for solving convex distributed optimisation problems. This Thesis presents a formulation of the ADMM that is guaranteed to converge if the communications among agents are faulty and the agents perform updates asynchronously. With strongly convex costs, the proposed algorithm is shown to converge exponentially fast. The further extension to partition-based problems is presented.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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