Computing Distances between Convex Sets and Subsets of the Positive Semideenite Matrices
نویسنده
چکیده
We describe an important class of semideenite programming problems that has received scant attention in the optimization community. These problems are derived from considerations in distance geometry and multidimensional scaling and therefore arise in a variety of disciplines, e.g. computational chemistry and psychometrics. In most applications, the feasible positive semideenite matrices are restricted in rank, so that recent interior-point methods for semideenite programming do not apply. We establish some theory for these problems and discuss what remains to be accomplished.
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