Distributed Approximation Algorithms is a class of algorithms in distributed computing that solve optimization problems by achieving near-optimal solutions through localized computation and communication among processors, distinguished by their bounded approximation ratios and coordination under resource constraints such as time, message complexity, or network topology.
332
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18.7K
Citations
695
Authors
297
Institutions
Publications per year
2017–2026
74
Parents
Publications
332
1–5 of 332
Authors
695
- FK
15
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- RW
11
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- TM
10
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- MG
9
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- PW
8
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1–5 of 695
Institutions
297
ETH Zurich
Zurich, Switzerland
21 h-index
42 publications
3.8K citations
Massachusetts Institute of Technology
Cambridge, United States
13 h-index
23 publications
2.1K citations
University of California, Berkeley
Berkeley, United States
12 h-index
24 publications
1.7K citations
Carnegie Mellon University
Pittsburgh, United States
10 h-index
18 publications
631 citations
Tel Aviv University
Tel Aviv, Israel
10 h-index
16 publications
350 citations
Illinois Institute of Technology
Chicago, United States
9 h-index
22 publications
5.7K citations
Centre National de la Recherche Scientifique
Paris, France
9 h-index
16 publications
875 citations
Stanford University
Stanford, United States
8 h-index
14 publications
1.6K citations
1–8 of 297
Venues
- arXiv (Cornell University)
Repository · 14 publications · 422 citations
12
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- SIAM Journal on Computing
12 publications · 760 citations
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- IEEE/ACM Transactions on Networking
TON · 9 publications · 442 citations
9
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- Journal of Parallel and Distributed Computing
9 publications · 236 citations
9
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- DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)
Repository · 7 publications · 134 citations
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