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Generic nondegeneracy in convex optimization

Dmitriy Drusvyatskiy (dd379***at***cornell.edu)
Adrian S. Lewis (aslewis***at***orie.cornell.edu)

Abstract: We show that minimizers of convex functions subject to almost all linear perturbations are nondegenerate. An analogous result holds more generally, for lower-C^2 functions.

Keywords: Convex, normal cone, subdifferential, Hausdorff measure, lower-C^2

Category 1: Convex and Nonsmooth Optimization (Convex Optimization )

Category 2: Convex and Nonsmooth Optimization (Nonsmooth Optimization )

Citation: Cornell University, School of Operations Research and Information Engineering, 206 Rhodes Hall Cornell University Ithaca, NY 14853. May 2010.

Download: [PDF]

Entry Submitted: 05/06/2010
Entry Accepted: 05/06/2010
Entry Last Modified: 05/06/2010

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