Distributed Optimization
Distributed Optimization is a methodological framework within distributed algorithms that enables the collaborative minimization or maximization of a global objective function by coordinating computational agents over a network, distinguished by its decomposition of the optimization task across multiple nodes that communicate and synchronize iteratively to achieve consensus or convergence without centralized control.
2.8K
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209.3K
Citations
4.6K
Authors
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Publications per year
2017–2026
1.6K
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Large Scale Distributed Deep Networks
Jay B. Dean, Greg S. Corrado, Rajat Monga et al. · 2012 · 2.9K citations
Fast linear iterations for distributed averaging
Lin Xiao, Stephen Boyd · Systems & Control Letters · 2004 · 2.8K citations
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University of Illinois Urbana-Champaign, United States
48 publications · 10.7K citations
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1.2K
Massachusetts Institute of Technology
Cambridge, United States
43 h-index
141 publications
28.8K citations
Nanyang Technological University
Singapore, Singapore
40 h-index
137 publications
9.7K citations
University of Illinois Urbana-Champaign
Urbana, United States
39 h-index
130 publications
21K citations

Southeast University
Nanjing, China
38 h-index
184 publications
9.7K citations
Carnegie Mellon University
Pittsburgh, United States
35 h-index
116 publications
9K citations
École Polytechnique Fédérale de Lausanne
Lausanne, Switzerland
34 h-index
107 publications
7.2K citations

Chinese Academy of Sciences
Beijing, China
33 h-index
86 publications
6.6K citations
Tsinghua University
Beijing, China
33 h-index
114 publications
9K citations
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230 publications · 31.7K citations
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104 publications · 11.1K citations
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Repository · 204 publications · 9.2K citations
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68 publications · 4.4K citations
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60 publications · 4.9K citations
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