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- W4296252005 abstract "Recently, distributed optimization has drawn significant attention in signal processing [1], due to the requirement to obtain decentralized control and decision making in sensor networks as well as large-scale data processing and learning. Because the distributed agents/nodes only process the local data and the information exchanged from direct neighbors, distributed optimization fits well for the applications where the data are received distributively [2] or the data privacy is of primary importance [3]." @default.
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- W4296252005 date "2022-09-19" @default.
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- W4296252005 title "Distributed Mathematical Optimization" @default.
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- W4296252005 doi "https://doi.org/10.1007/978-981-19-2016-5_5" @default.
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