Results 1 to 10 of about 233,364 (265)
A survey of distributed optimization
Annual Reviews in Control, 2019 In distributed optimization of multi-agent systems, agents cooperate to minimize a global function which is a sum of local objective functions.
Tao Yang, Xinlei Yi, Junfeng Wu
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DISTRIBUTED QUERY OPTIMIZATION [PDF]
Analele Universităţii Constantin Brâncuşi din Târgu Jiu : Seria Economie, 2010 The need for the distributed systems has been determined by the type of business developed by companies with offices geographically distributed where the specific organizational structure promotes a decentralized business model.
Nicoleta IACOB
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Resilient Distributed Optimization*
2023 American Control Conference (ACC), 2023 This version fixes the incorrect statements of Proposition 3 and Theorem 2 in the last ...
Jingxuan Zhu +3 more
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Machine learning techniques for classifying dangerous asteroids
MethodsX, 2023 There is an infinite number of objects in outer space, and these objects and asteroids might be harmful. Hence, it is wise to know what is surrounding us and what can harm us amongst those.Therefore, in this article, with the hyperparameters tuning of ...
Seyed Matin Malakouti +2 more
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Learning (With) Distributed Optimization
CoRR, 2023 23 ...
Aadharsh Aadhithya A +6 more
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Impacts of Energy Flexibility in Transactive Energy Systems With Large-Scale Renewable Generation
IEEE Access, 2022 Modern-day energy systems are evolving to be complex, interconnected, and transactive systems without clear demarcation between energy “producers” and “consumers”.
Saptarshi Bhattacharya +3 more
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Single-Image Reflection Removal Using Deep Learning: A Systematic Review
IEEE Access, 2022 Images captured through the glass often consist of undesirable specular reflections. These reflections detected in front of the glass remarkably reduce the quality and visibility of the scenes behind it.
Ali Amanlou +4 more
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Hardness of Distributed Optimization [PDF]
Proceedings of the 2019 ACM Symposium on Principles of Distributed Computing, 2019 This paper studies lower bounds for fundamental optimization problems in the CONGEST model. We show that solving problems exactly in this model can be a hard task, by providing $\tildeΩ(n^2)$ lower bounds for cornerstone problems, such as minimum dominating set (MDS), Hamiltonian path, Steiner tree and max-cut.
Nir Bachrach +5 more
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On the Optimization of Margin Distribution
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022 Margin has played an important role on the design and analysis of learning algorithms during the past years, mostly working with the maximization of the minimum margin. Recent years have witnessed the increasing empirical studies on the optimization of margin distribution according to different statistics such as medium margin, average margin, margin ...
Meng-Zhang Qian +3 more
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Distributed Optimization for Second-Order Multi-Agent Systems over Directed Networks
Mathematics, 2022 This paper studies a generalized distributed optimization problem for second-order multi-agent systems (MASs) over directed networks. Firstly, an improved distributed continuous-time algorithm is proposed.
Feiyang Yang +3 more
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