Joint Optimization
Joint Optimization is an academic method that integrates multiple interdependent components or objectives into a unified framework to simultaneously optimize their performance, thereby distinguishing itself from sequential or isolated optimization approaches by leveraging synergies across coupled subproblems.
3.3K
Publications
171K
Citations
8.9K
Authors
1.7K
Institutions
Publications per year
2017–2026
2.2K
Parents
3.3K
Albert Greenberg, James R. Hamilton, David A. Maltz et al. · ACM SIGCOMM Computer Communication Review · 2008 · 1.6K citations · Full text
Sparse Gaussian Processes using Pseudo-inputs
Edward Snelson, Zoubin Ghahramani · 2005 · 1.3K citations
David Gesbert, Marios Kountouris, Robert W. Heath et al. · IEEE Signal Processing Magazine · 2007 · 1.1K citations
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Singapore University of Technology and Design, Singapore
19 publications · 1K citations
17
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1.7K

Southeast University
Nanjing, China
43 h-index
223 publications
13.9K citations

Beijing University of Posts and Telecommunications
Beijing, China
43 h-index
410 publications
22.2K citations

Xidian University
Xi'an, China
38 h-index
236 publications
10K citations

Shanghai Jiao Tong University
Shanghai, China
38 h-index
246 publications
10.2K citations
Tsinghua University
Beijing, China
36 h-index
198 publications
8.6K citations

University of Electronic Science and Technology of China
Chengdu, China
34 h-index
177 publications
8K citations
Nanjing University of Posts and Telecommunications
Nanjing, China
33 h-index
135 publications
7.7K citations

Carleton University
Ottawa, Canada
32 h-index
48 publications
4.5K citations
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152 publications · 10.5K citations
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172 publications · 10.3K citations
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108 publications · 7.7K citations
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110 publications · 6.3K citations
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104 publications · 4.6K citations
39
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