Matrix Permutation Optimization
Matrix Permutation Optimization is a computational method that belongs to the class of matrix reorganization techniques, specifically distinguished by its objective to rearrange the rows and columns of an adjacency matrix through permutation operations in order to optimize a defined structural or visual quality criterion.
32
Publications
2.9K
Citations
90
Authors
58
Institutions
Publications per year
2017–2026
7
32
Patrick Amestoy, Timothy A. Davis, Iain Duff · ACM Transactions on Mathematical Software · 2004 · 314 citations
Learning by Associating Ambiguously Labeled Images
Zinan Zeng, Shijie Xiao, Kui Jia et al. · 2013 · 147 citations
1–5 of 32
90
Centre Européen de Recherche et de Formation Avancée en Calcul Scientifique, France
2 publications · 361 citations
2
h-index
2
h-index
2
h-index
1
h-index
1
h-index
1–5 of 90
58
University of California, Berkeley
Berkeley, United States
2 h-index
3 publications
61 citations
Florida State University
Tallahassee, United States
2 h-index
3 publications
142 citations
Universidade Federal de Minas Gerais
Belo Horizonte, Brazil
1 h-index
4 publications
72 citations

University of Hong Kong
Pok Fu Lam, Hong Kong
1 h-index
1 publications
21 citations
The Ohio State University
Columbus, United States
1 h-index
5 publications
85 citations
Peng Cheng Laboratory
Shenzhen, China
1 h-index
2 publications
26 citations

Vrije Universiteit Amsterdam
Amsterdam, The Netherlands
1 h-index
1 publications
24 citations
IBM Research - Almaden
San Jose, United States
1 h-index
1 publications
18 citations
1–8 of 58
2 publications · 127 citations
2
h-index
2 publications · 55 citations
2
h-index
1 publications · 39 citations
1
h-index
1 publications · 39 citations
1
h-index
1 publications · 63 citations
1
h-index
1–5