Taking All Positive Eigenvectors Is Suboptimal in Classical Multidimensional Scaling

DOI10.1137/15M102602XzbMath1351.91020arXiv1402.2703OpenAlexW3105139756MaRDI QIDQ2828334

Rajesh Pereira, Jeffrey Tsang

Publication date: 25 October 2016

Published in: SIAM Journal on Optimization (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1402.2703

zbMATH Keywords

quadratic programmingconvex optimizationdimensionality reductionmultidimensional scalingclassical multidimensional scaling

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Quadratic programming (90C20) One- and multidimensional scaling in the social and behavioral sciences (91C15)

Uses Software

• Matlab
• R

Cites Work

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• The analytical solution of the additive constant problem
• Interior path following primal-dual algorithms. II: Convex quadratic programming
• Modern multidimensional scaling. Theory and applications.
• Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis
• Remarks to Maurice Frechet's article ``Sur la definition axiomatique d'une classe d'espaces vectoriels distancies applicables vectoriellement sur l'espace de Hilbert
• Euclidean Distance Matrices and Applications
• Some properties of clasical multi-dimesional scaling

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