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Global Minima by Penalized Full-dimensional Scaling
- Publication Year :
- 2024
-
Abstract
- The full-dimensional (metric, Euclidean, least squares) multidimensional scaling stress loss function is combined with a quadratic external penalty function term. The trajectory of minimizers of stress for increasing values of the penalty parameter is then used to find (tentative) global minima for low-dimensional multidimensional scaling. This is illustrated with several one-dimensional and two-dimensional examples.<br />Comment: 39 pages
- Subjects :
- Statistics - Computation
Statistics - Machine Learning
62-04 62-08
G.3
Subjects
Details
- Database :
- arXiv
- Publication Type :
- Report
- Accession number :
- edsarx.2407.16645
- Document Type :
- Working Paper