Smoothing a polyhedral convex function via cumulant transformation and homogenization
Alberto Seeger
Annales Polonici Mathematici, Tome 66 (1997), p. 259-268 / Harvested from The Polish Digital Mathematics Library

Given a polyhedral convex function g: ℝⁿ → ℝ ∪ +∞, it is always possible to construct a family gt>0 which converges pointwise to g and such that each gₜ: ℝⁿ → ℝ is convex and infinitely often differentiable. The construction of such a family gt>0 involves the concept of cumulant transformation and a standard homogenization procedure.

Publié le : 1997-01-01
EUDML-ID : urn:eudml:doc:270164
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Alberto Seeger. Smoothing a polyhedral convex function via cumulant transformation and homogenization. Annales Polonici Mathematici, Tome 66 (1997) pp. 259-268. http://gdmltest.u-ga.fr/item/bwmeta1.element.bwnjournal-article-apmv67z3p259bwm/

[000] [1] O. Barndorff-Nielsen, Exponential families: exact theory, Various Publ. Ser. 19, Inst. of Math., Univ. of Aarhus, Denmark, 1970. | Zbl 0249.62006

[001] [2] A. Ben-Tal and M. Teboulle, A smoothing technique for nondifferentiable optimization problems, in: Lecture Notes in Math. 1405, S. Dolecki (ed.), Springer, Berlin, 1989, 1-11. | Zbl 0683.90078

[002] [3] D. Bertsekas, Constrained Optimization and Lagrangian Multiplier Methods, Academic Press, New York, 1982.

[003] [4] C. Davis, All convex invariant functions of hermitian matrices, Arch. Math. (Basel) 8 (1957), 276-278. | Zbl 0086.01702

[004] [5] R. A. El-Attar, M. Vidyasagar, and S. R. K. Dutta, An algorithm for l₁-norm minimization with application to nonlinear l₁-approximation, SIAM J. Numer. Anal. 16 (1979), 70-86. | Zbl 0401.90089

[005] [6] R. Ellis, Entropy, Large Deviations and Statistical Mechanics, Springer, Berlin, 1985.

[006] [7] C. Lemaréchal and C. Sagastizábal, Practical aspects of the Moreau-Yosida regularization: theoretical preliminaries, SIAM J. Optim. 7 (1997), 367-385. | Zbl 0876.49019

[007] [8] A. S. Lewis, Convex analysis on the Hermitian matrices, SIAM J. Optim. 6 (1996), 164-177. | Zbl 0849.15013

[008] [9] J. E. Martinez-Legaz, On convex and quasiconvex spectral functions, in: Proc. 2nd Catalan Days on Appl. Math., M. Sofonea and J. N. Corvellec (eds.), Presses Univ. de Perpignan, Perpignan, 1995, 199-208. | Zbl 0911.90277

[009] [10] M. L. Overton and R. S. Womersley, Optimality conditions and duality theory for minimizing sums of the largest eigenvalues of symmetric matrices, Math. Programming 62 (1993), 321-357. | Zbl 0806.90114

[010] [11] R. T. Rockafellar, Convex Analysis, Princeton Univ. Press, Princeton, N.J., 1970. | Zbl 0193.18401

[011] [12] A. Seeger, Smoothing a nondifferentiable convex function: the technique of the rolling ball, Technical Report 165, Dep. of Mathematical Sciences, King Fahd Univ. of Petroleum and Minerals, Dhahran, Saudi Arabia, October 1994. | Zbl 0921.49008

[012] [13] A. Seeger, Convex analysis of spectrally defined matrix functions, SIAM J. Optim. 7 (1997), 679-696. | Zbl 0890.15018