Journal of Mathematical Imaging and Vision

, Volume 56, Issue 2, pp 175–194 | Cite as

Techniques for Gradient-Based Bilevel Optimization with Non-smooth Lower Level Problems

  • Peter Ochs
  • René Ranftl
  • Thomas Brox
  • Thomas Pock
Article

Abstract

We propose techniques for approximating bilevel optimization problems with non-smooth lower level problems that can have a non-unique solution. To this end, we substitute the expression of a minimizer of the lower level minimization problem with an iterative algorithm that is guaranteed to converge to a minimizer of the problem. Using suitable non-linear proximal distance functions, the update mappings of such an iterative algorithm can be differentiable, notwithstanding the fact that the minimization problem is non-smooth.

Keywords

Bilevel optimization Non-smooth lower level problem Bregman proximity function 

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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Peter Ochs
    • 1
    • 3
  • René Ranftl
    • 2
  • Thomas Brox
    • 3
  • Thomas Pock
    • 4
    • 5
  1. 1.Mathematical Image Analysis GroupUniversity of SaarlandSaarbrückenGermany
  2. 2.Visual Computing LabIntel LabsSanta ClaraUSA
  3. 3.Computer Vision GroupUniversity of FreiburgFreiburg im BreisgauGermany
  4. 4.Institute for Computer Graphics and VisionGraz University of TechnologyGrazAustria
  5. 5.Digital Safety & Security DepartmentAIT Austrian Institute of Technology GmbHViennaAustria

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