Data Approximation
Data Approximation is a methodological framework within geometric approximation that specifically enables the simplification or representation of complex, high-dimensional datasets through lower-dimensional geometric structures while preserving essential data properties.
405
Publications
30.9K
Citations
877
Authors
415
Institutions
Publications per year
2017–2026
72
Parents
405
Networks for approximation and learning
Tomaso Poggio, Federico Girosi · Proceedings of the IEEE · 1990 · 3.3K citations
Data Analysis in Community and Landscape Ecology.
M. O. Hill, R.H.G. Jongman, Cajo J. F. ter Braak et al. · Journal of Applied Ecology · 1988 · 1.2K citations
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877
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415
Massachusetts Institute of Technology
Cambridge, United States
11 h-index
22 publications
7.4K citations
Princeton University
Princeton, United States
9 h-index
16 publications
7.9K citations
Institut national de recherche en sciences et technologies du numérique
Le Chesnay-Rocquencourt, France
8 h-index
12 publications
600 citations
Stanford University
Stanford, United States
8 h-index
20 publications
1.1K citations
RWTH Aachen University
Aachen, Germany
7 h-index
19 publications
596 citations

University of Auckland
Auckland, New Zealand
7 h-index
7 publications
721 citations
University of Illinois Urbana-Champaign
Urbana, United States
6 h-index
15 publications
1.1K citations

Tel Aviv University
Tel Aviv, Israel
6 h-index
12 publications
779 citations
1–8 of 415
Repository · 15 publications · 413 citations
11
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7 publications · 290 citations
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6 publications · 258 citations
6
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5 publications · 254 citations
5
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4 publications · 136 citations
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