Finding the minimum and the minimizers of convex functions has been of primary concern in convex analysis since its conception. It is well-known that if a convex function has a minimum, then that minimum is global. The minimizers, however, may not be unique. There are certain subclasses, such as strictly convex functions, that do have unique minimizers when the minimum exists, but other subclasses, such as constant functions, that do not. This paper addresses the question of how many convex functions have unique minimizers. We show, using Baire category theory, that the set of proximal mappings of convex functions that have a unique fixed point is generic. Consequently, the set of classes of convex functions that have unique minimizers is generic.

Contact details are reproduced from the original publication and may be historical.

Chayne Planiden

Dept. of Mathematics, University of British Columbia, Okanagan Campus, 3333 University Way, Kelowna, BC, Canada V1V 1V7

chayneplaniden@hotmail.com

Xianfu Wang

Dept. of Mathematics, University of British Columbia, Okanagan Campus, 3333 University Way, Kelowna, BC, Canada V1V 1V7

shawn.wang@ubc.ca
  1. H. Attouch, R. Lucchetti, R. J.-B. Wets: The topology of the ρ-Hausdorff distance, Ann. Mat. Pura Appl., IV. Ser. 160 (1991) 303–320.https://doi.org/10.1007/BF01764131Google Scholar
  2. H. Attouch, R. J.-B. Wets: Quantitative stability of variational systems. I. The epigraphical distance, Trans. Amer. Math. Soc. 328(2) (1991) 695–729.https://doi.org/10.1090/S0002-9947-1991-1018570-0Google Scholar
  3. S. Bartz, H. Bauschke, J. Borwein, S. Reich, X. Wang: Fitzpatrick functions, cyclic monotonicity and Rockafellar’s antiderivative, Nonlinear Anal. 66(5) (2007) 1198–1223.https://doi.org/10.1016/j.na.2006.01.013Google Scholar
  4. H. Bauschke, P. Combettes: Convex Analysis and Monotone Operator Theory in Hilbert Spaces, CMS Books in Mathematics, Springer, New York (2011).https://doi.org/10.1007/978-1-4419-9467-7Google Scholar
  5. J. Borwein, J. Vanderwerff: Convex Functions: Constructions, Characterizations and Counterexamples, Encyclopedia of Mathematics and its Applications 109, Cambridge University Press, Cambridge (2010).https://doi.org/10.1017/CBO9781139087322Google Scholar
  6. J. Borwein, Q. Zhu: Techniques of Variational Analysis, CMS Books in Mathematics 20, Springer, New York (2005).Google Scholar
  7. P. Combettes, V. Wajs: Signal recovery by proximal forward-backward splitting, Multiscale Model. Simul. 4(4) (2005) 1168–1200.https://doi.org/10.1137/050626090Google Scholar
  8. R. Lucchetti: Convexity and Well-Posed Problems, CMS Books in Mathematics 22, Springer, New York (2006).https://doi.org/10.1007/0-387-31082-7Google Scholar
  9. J.-J. Moreau: Proximité et dualité dans un espace hilbertien, Bull. Soc. Math. Fr. 93 (1965) 273–299.https://doi.org/10.24033/bsmf.1625Google Scholar
  10. J.-J. Moreau: Fonctionnelles convexes, Séminaire Jean Leray 2 (1966–67) 1–108.Google Scholar
  11. S. Reich, A. Zaslavski: Genericity in Nonlinear Analysis, Developments in Mathematics 34, Springer, New York (2014).https://doi.org/10.1007/978-1-4614-9533-8Google Scholar
  12. R. T. Rockafellar: Monotone operators and the proximal point algorithm, SIAM J. Control Optim. 14(5) (1976) 877–898.https://doi.org/10.1137/0314056Google Scholar
  13. R. T. Rockafellar: Convex Analysis, Princeton Landmarks in Mathematics, Princeton University Press, Princeton (1997).Google Scholar
  14. R. T. Rockafellar, R. J.-B. Wets: Variational Analysis, Grundlehren der Mathematischen Wissenschaften 317, Springer, Berlin (1998).https://doi.org/10.1007/978-3-642-02431-3Google Scholar
  15. M. Searcóid: Metric Spaces, Springer Undergraduate Mathematics Series, Springer, London (2006).Google Scholar
  16. K. Stromberg: An Introduction to Classical Real Analysis, Wadsworth International Mathematical Series, Wadsworth, Belmont (1981).Google Scholar
  17. X. Wang: Most maximally monotone operators have a unique zero and a super-regular resolvent, Nonlinear Anal. 87 (2013) 69–82.https://doi.org/10.1016/j.na.2013.03.008Google Scholar

C. Planiden, X. Wang. “Most Convex Functions Have Unique Minimizers.” Journal of Convex Analysis 23 (2016), No. 3, 877–892. https://doi.org/10.68381/jca23033