Group for Research in Decision Analysis

Approximate subdifferential computation in computational convex analysis

Yves Lucet The University of British Columbia, Canada

Computational convex analysis focuses on the computation of convex operators that routinely appear in convex analysis e.g. Legendre-Fenchel conjugate, Moreau envelope, etc. It has found applications in image processing, partial differential equations (solving Hamilton–Jacobi equations and using differential equations numerical schemes to compute the convex envelope), max-plus algebra, computer vision, robot navigation, thermodynamics, electrical networks, medical imaging, and network communication.

After presenting what computation the (open source) CCA numerical library allows, we will switch the focus from convex transforms like the Legendre-Fenchel transform to convex operators like the subdifferential. We will present results on efficiently computing the approximate subdifferential of a convex univariate function.

Joint work with W. Hare, A. Bajaj, and D. Kumar.

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