Abstract
Approximation of convex sets takes a major role in optimization theory and practice. Approximation by semidefinite representable set draws more attention as semidefinite programming problems can be solved very efficiently using numerous existing algorithms. We contribute a technique by which a closed convex set can be approximated by a compactly semidefinite representable set. Further, we extend the technique of approximation and we prove that a closed convex set can be approximated by semidefinite representable set. These results give new techniques in semidefinite programming.
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Ghosh, A., Narayanan, V. (2019). Semidefinite Approximation of Closed Convex Set. In: Deep, K., Jain, M., Salhi, S. (eds) Decision Science in Action. Asset Analytics. Springer, Singapore. https://doi.org/10.1007/978-981-13-0860-4_20
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DOI: https://doi.org/10.1007/978-981-13-0860-4_20
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