Semisupervised learning from dissimilarity data

DOI10.1016/J.CSDA.2008.02.030zbMath1452.62133DBLPjournals/csda/TrossetPPM08OpenAlexW2137304241WikidataQ33560747 ScholiaQ33560747MaRDI QIDQ1023817

Michael I. Miller, Michael W. Trosset, Youngser Park, Carey E. Priebe

Publication date: 16 June 2009

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc2856100

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Classification and discrimination; cluster analysis (statistical aspects) (62H30)

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Cites Work

• The out-of-sample problem for classical multidimensional scaling
• Classification, pattern recognition and reduction of dimensionality
• Modern multidimensional scaling: theory and applications
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• Computing large deformation metric mappings via geodesic flows of diffeomorphisms
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• Some distance properties of latent root and vector methods used in multivariate analysis
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