Sammon Mapping
Sammon Mapping is a nonlinear dimensionality reduction technique that preserves the structure of interpoint distances in high-dimensional data by minimizing a stress function based on pairwise dissimilarities between points in the original and lower-dimensional spaces.
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38.3K
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185
Authors
95
Institutions
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2017–2026
8
Variants
Sammon's Mapping
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Laurens van der Maaten, Geoffrey E. Hinton · Journal of Machine Learning Research · 2008 · 35.7K citations
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Delft University of Technology
Delft, The Netherlands
3 h-index
4 publications
227 citations
Ben-Gurion University of the Negev
Beersheba, Israel
2 h-index
8 publications
319 citations
Stanford University
Stanford, United States
2 h-index
2 publications
58 citations
Veszprémi Érseki Hittudományi Fõiskola
Veszprém, Hungary
2 h-index
4 publications
83 citations
AGH University of Krakow
Krakow, Poland
2 h-index
3 publications
49 citations

University of Auckland
Auckland, New Zealand
1 h-index
2 publications
78 citations

City University of Hong Kong
Hong Kong, Hong Kong
1 h-index
1 publications
570 citations

Kwangwoon University
Seoul, South Korea
1 h-index
2 publications
28 citations
1–8 of 95
3 publications · 301 citations
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Conference · 2 publications · 30 citations
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2 publications · 80 citations
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2 publications · 26 citations
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2 publications · 37 citations
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