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Cited by 5Distributed Control Multi-Agent SystemsAdvanced Control Systems OptimizationOptimal Power Flow Distribution

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Augmented distributed optimization for networked systems

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Xu, Jinming·2019
DOI 10.32657/10356/68805
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  • The DIGing algorithm is a minor variation of algorithms that have appeared in [73,74] and [15-17].

    “The algorithm we will study in this paper crucially relies on tracking differences of gradients and is a minor variation of algorithms that have appeared in [73,74] and [15-17].”

    From Achieving Geometric Convergence for Distributed Optimization Over Time-Varying Graphs (2017) · cites this paper as [73]

    Section 5.4 describes AugDGM as using dynamic average consensus to track gradients through their differences, supporting the claimed algorithmic resemblance. Our copy does not identify DIGing or establish that it is a minor variation of AugDGM or the other cited algorithms. No page number is available for the indexed passage. (LLM, conf=0.77)

    Experimental — accuracy not yet measured

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Metadata

Authors
Xu, J.
Corresponding author
Xu, Jinming
ORCID
Xu, Jinming
Publisher
Nanyang Technological University
Published
2016-01-01
DOI
10.32657/10356/68805
OpenAlex
W2412784992
Cited by
5
References
3
Citations by year
2019: 1 · 2018: 4
Type
dissertation
Language
en
Open access
Locations
DR-NTU (Nanyang Technological University) (submittedVersion)
Topics
  • Physical Sciences › Engineering › Control and Systems Engineering › Distributed Control Multi-Agent Systems
  • Physical Sciences › Engineering › Control and Systems Engineering › Advanced Control Systems Optimization
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Optimal Power Flow Distribution
Keywords
distributed optimization, networked systems

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