Abstract
Motivated by the metricsstress problem in multidimensional scaling, the authors consider the more general problem of minimizing a strictly convex function on a particular subset ofR n × n. The subset in question is the intersection of a linear subspace with the symmetric positive-semidefinite matrices of rank ≤p. Because of the rank restriction, this subset is not convex. Several equivalent formulations of this problem are derived, and the advantages and disadvantages of each formulation are discussed.
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Communicated by R. A. Tapia
Part of this research was conducted while the authors were visitors at the Center for Research on Parallel Computation, Rice University, Houston, Texas. The first author was partially supported by National Science Foundation Grant RII-89-05080.
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Tarazaga, P., Trosset, M.W. An optimization problem on subsets of the symmetric positive-semidefinite matrices. J Optim Theory Appl 79, 513–524 (1993). https://doi.org/10.1007/BF00940556
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DOI: https://doi.org/10.1007/BF00940556