Abstract
Totally convex functions and Bregman projections associated to them are of special interest for building optimization and feasibility algorithms. This motivates one to investigate existence of totally convex functions in Banach spaces. Also, this raises the question whether and under which conditions the corresponding Bregman projections have the properties needed for guaranteeing convergence and stability of the algorithms based on them. We show that a reflexive Banach space in which some power of the norm is totally convex is an E-space and conversely. Also we prove that totally convex functions in reflexive Banach spaces are necessarily essentially strictly convex in the sense of H. H. Bauschke, J. M. Borwein, and P. L. Combettes ["Essential smoothness, essential strict convexity, and Legendre functions in Banach spaces", Commun. Contemp. Math. 3(4) (2001) 615–647]. We use these facts in order to establish continuity and stability properties of Bregman projections.
References
- Y. Alber: Metric and generalized projection operators in Banach spaces: Properties and applications, in: Theory and Applications of Nonlinear Operators of Accretive and Monotone Type, Dekker, New York (1996) 15–50.Google Scholar
- Y. Alber, D. Butnariu: Convergence of Bregman projection methods for solving consistent convex feasibility problems in reflexive Banach spaces, J. Optimization Theory Appl. 92(1) (1997) 33–61.https://doi.org/10.1023/A:1022631928592Google Scholar
- Y. Alber, D. Butnariu, I. Ryazantseva: Regularization methods for ill-posed inclusions and variational inequalities with domain perturbations, J. Nonlinear Convex Anal. 1(2) (2001) 53–79.Google Scholar
- V. Barbu, Th. Precupanu: Convexity and Optimization in Banach Spaces, D. Reidel Publishing Co., Dordrecht, 2nd edition (1986).Google Scholar
- H. H. Bauschke, J. M. Borwein: Legendre functions and the method of random Bregman projections, J. Convex Anal. 4(1) (1997) 27–67.https://doi.org/10.68381/jca04002Google Scholar
- H. H. Bauschke, J. M. Borwein, P. L. Combettes: Essential smoothness, essential strict convexity, and Legendre functions in Banach spaces, Commun. Contemp. Math. 3(4) (2001) 615–647.https://doi.org/10.1142/S0219199701000524Google Scholar
- H. H. Bauschke, P. L. Combettes: Construction of best Bregman approximations in reflexive Banach spaces, Proc. Am. Math. Soc. 31(12) (2003) 3757–3766.https://doi.org/10.1090/S0002-9939-03-07050-3Google Scholar
- H. H. Bauschke, A. S. Lewis: Dykstra’s algorithm with Bregman projections: A convergence proof, Optimization 48 (2000) 409–427.https://doi.org/10.1080/02331930008844513Google Scholar
- C. Bessaga, A. Pelczyński: Selected Topics in Infinite-Dimensional Topology, PWN-Polish Scientific Publishers, Warszawa (1975).Google Scholar
- L. M. Bregman: The relaxation method for finding common points of convex sets and its application to the solution of problems in convex programming, USSR Computational Mathematics and Mathematical Physics 7 (1967) 200–217.https://doi.org/10.1016/0041-5553(67)90040-7Google Scholar
- R. S. Burachik: Generalized Proximal Point Methods for the Variational Inequality Problem, PhD Thesis, Instituto de Mathematica Pura e Aplicada (IMPA), Rio de Janeiro, RJ, Brazil (1995).Google Scholar
- R. S. Burachik, S. Scheimberg: A proximal point method for the variational inequality problem in Banach spaces, SIAM J. Control Optim. 39(5) (2001) 1633–1649.https://doi.org/10.1137/S0363012998339745Google Scholar
- D. Butnariu, Y. Censor, S. Reich: Iterative averaging of entropic projections for solving stochastic convex feasibility problems, Comput. Optim. Appl. 8 (1997) 21–39.https://doi.org/10.1023/A:1008654413997Google Scholar
- D. Butnariu, A. N. Iusem: Totally Convex Functions for Fixed Points Computation and Infinite Dimensional Optimization, Kluwer Academic Publishers, Dordrecht (2000).https://doi.org/10.1007/978-94-011-4066-9Google Scholar
- D. Butnariu, A. N. Iusem: Local moduli of convexity and their application to finding almost common fixed points of measurable families of operators, in: Recent Developments in Optimization Theory and Nonlinear Analysis, Y. Censor, S. Reich (eds.), Contemp. Math. 204 (1997) 61–92.https://doi.org/10.1090/conm/204/02623Google Scholar
- D. Butnariu, A. N. Iusem: On a proximal point method for convex optimization in Banach spaces, Numer. Funct. Anal. Optimization 18 (1998) 723–744.https://doi.org/10.1080/01630569708816788Google Scholar
- D. Butnariu, A. N. Iusem, R. S. Burachik: Iterative methods for solving stochastic convex feasibility problems and applications, Comput. Optim. Appl. 15 (2000) 269–307.https://doi.org/10.1023/A:1008795702124Google Scholar
- D. Butnariu, A. N. Iusem, E. Resmerita: Total convexity for powers of the norm in uniformly convex Banach spaces, J. Convex Anal. 7 (2000) 319–334.https://doi.org/10.68381/jca07016Google Scholar
- D. Butnariu, A. N. Iusem, C. Zălinescu: On uniform convexity, total convexity and convergence of the proximal point and outer Bregman projection algorithms in Banach spaces, J. Convex Anal. 10(1) (2003) 35–61.https://doi.org/10.68381/jca1002Google Scholar
- D. Butnariu, S. Reich, A. Zaslavski: Weak convergence of orbits of nonlinear operators in reflexive Banach spaces, Numer. Funct. Anal. Optimization 24 (2003) 489–508.https://doi.org/10.1081/NFA-120023869Google Scholar
- D. Butnariu, E. Resmerita: The outer Bregman projection method for stochastic feasibility problems in Banach spaces, in: Inherently Parallel Algorithms for Feasibility and Optimization and their Applications, D. Butnariu, Y. Censor, S. Reich (eds.), Elsevier, Amsterdam, Stud. Comput. Math. 8 (2001) 69–86.https://doi.org/10.1016/S1570-579X(01)80007-0Google Scholar
- Y. Censor, A. Lent: An iterative row action method for interval convex programming, J. Optimization Theory Appl. 34 (1981) 321–353.https://doi.org/10.1007/BF00934676Google Scholar
- Y. Censor, S. Zenios: Parallel Optimization: Theory, Algorithms and Applications, Oxford University Press, New York (1997).Google Scholar
- I. Ciorănescu: Geometry of Banach Spaces, Duality mappings, and Nonlinear Problems, Kluwer Academic Publishers, Dordrecht (1990).https://doi.org/10.1007/978-94-009-2121-4Google Scholar
- R. Deville, G. Godefroy, V. Zizler: Smoothness and Renormings in Banach Spaces, Longman Scientific & Technical, Harlow (1993).Google Scholar
- A. L. Dontchev, T. Zolezzi: Well-Posed Optimization Problems, Springer-Verlag, Berlin (1993).https://doi.org/10.1007/BFb0084195Google Scholar
- J. Eckstein: Nonlinear proximal point algorithms using Bregman functions, with applications to convex programming, Math. Oper. Res. 18(1) (1993) 202–226.https://doi.org/10.1287/moor.18.1.202Google Scholar
- K. Fan, I. Glicksberg: Some geometric properties of the spheres in a normed linear space, Duke Math. J. 25 (1958) 553–568.https://doi.org/10.1215/S0012-7094-58-02550-XGoogle Scholar
- R. Holmes: A Course on Optimization and Best Approximation, Lecture Notes in Mathematics 257, Springer (1972).https://doi.org/10.1007/BFb0059450Google Scholar
- A. N. Iusem, R. Gárciga-Otero: Inexact versions of proximal point and augmented Lagrangian algorithms in Banach spaces, Numer. Funct. Anal. Optimization 22 (2001) 609–640.https://doi.org/10.1081/NFA-100105310Google Scholar
- A. N. Iusem, R. Gárciga-Otero: Augmented Lagrangian methods for cone-constrained convex optimization in Banach spaces, J. Nonlinear Convex Analysis 3 (2002) 155–176.Google Scholar
- K. C. Kiwiel: Proximal minimization methods with generalized Bregman functions, SIAM J. Control Optimization 35(4) (1997) 1142–1168.https://doi.org/10.1137/S0363012995281742Google Scholar
- U. Mosco: Approximation of the solutions of some variational inequalities, Ann. Sc. Norm. Sup. Pisa 21 (1967) 373–394.Google Scholar
- J.-P. Penot, R. Ratsimahalo: Characterizations of metric projections in Banach spaces and applications, Abstr. Appl. Anal. 3 (1998) 85–103.https://doi.org/10.1155/S1085337598000451Google Scholar
- R. R. Phelps: Convex Functions, Monotone Operators and Differentiability, Springer Verlag, Berlin (1993).Google Scholar
- S. Reich: A weak convergence theorem for the alternating method with Bregman distances, in: Theory and Applications of Nonlinear Operators of Accretive and Monotone Type, Dekker, New York (1996) 313–318.Google Scholar
- R. T. Rockafellar: Convex Analysis, Princeton University Press, Princeton (1970).https://doi.org/10.1515/9781400873173Google Scholar
- M. V. Solodov, B. F. Svaiter: An inexact hybrid generalized proximal point algorithm and some new results on the theory of Bregman functions, Math. Oper. Res. 25(2) (2000) 214–230.https://doi.org/10.1287/moor.25.2.214.12222Google Scholar
- C. Zălinescu: Convex Analysis in General Vector Spaces, World Scientific, River Edge, N.J. (2002).https://doi.org/10.1142/5021Google Scholar
- C. Zălinescu: On uniformly convex functions, J. Math. Anal. Appl. 95 (1983) 344–374.https://doi.org/10.1016/0022-247X(83)90112-9Google Scholar
Suggested citation
Published by Heldermann Verlag, 2004. Rights now held by Banach Press LLC.
