@inproceedings{3c2c6e2209514a968e0031c972b5cdda,
title = "Distributed Global Optimization by Annealing",
abstract = "The paper considers distributed global minimization of a nonconvex function. We study a first-order consensus + innovations type algorithm that incorporates decaying additive Gaussian noise for annealing to converge to the set of global minima under certain technical assumptions. The paper presents simple methods for verifying that the required technical assumptions hold and illustrates it with a distributed target-localization application.",
author = "Brian Swenson and Soummya Kart and Poor, {H. Vincent} and Moura, {Jose M.F.}",
note = "Funding Information: The work of B. Swenson and H. V. Poor was partially supported by the Air Force Office of Scientific Research under MURI Grant FA9550-18-1-0502. The work of S. Kar and J. M. F. Moura was partially supported by the National Science Foundation (NSF) under NSF Grant CCF 1513936. Publisher Copyright: {\textcopyright} 2019 IEEE.; 8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2019 ; Conference date: 15-12-2019 Through 18-12-2019",
year = "2019",
month = dec,
doi = "10.1109/CAMSAP45676.2019.9022513",
language = "English (US)",
series = "2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2019 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "181--185",
booktitle = "2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2019 - Proceedings",
address = "United States",
}