On convex functions and the finite element method TeX Export

@misc{citeulike:2663082, abstract = {Many problems of theoretical and practical interest involve finding a convex or concave function. For instance, optimization problems such as finding the projection on the convex functions in \$H^k(\Omega)\$, or some problems in economics. In the continuous setting and assuming smoothness, the convexity constraints may be given locally by asking the Hessian matrix to be positive semidefinite, but in making discrete approximations two difficulties arise: the continuous solutions may be not smooth, and an adequate discrete version of the Hessian must be given. In this paper we propose a finite element description of the Hessian, and prove convergence under very general conditions, even when the continuous solution is not smooth, working on any dimension, and requiring a linear number of constraints in the number of nodes. Using semidefinite programming codes, we show concrete examples of approximations to optimization problems.}, archivePrefix = {arXiv}, author = {Aguilera, N\&\#xe9;stor and Morin, Pedro}, citeulike-article-id = {2663082}, citeulike-linkout-0 = {http://arxiv.org/abs/0804.1780}, citeulike-linkout-1 = {http://arxiv.org/pdf/0804.1780}, day = {10}, eprint = {0804.1780}, keywords = {afriat-varian, algorithm, convex, discrete, semidefinite}, month = {Apr}, posted-at = {2008-04-13 08:29:21}, priority = {2}, title = {On convex functions and the finite element method}, url = {http://arxiv.org/abs/0804.1780}, year = {2008} }

TY - ELEC ID - citeulike:2663082 L3 - citeulike-article-id:2663082 N2 - Many problems of theoretical and practical interest involve finding a convex or concave function. For instance, optimization problems such as finding the projection on the convex functions in $H^k(\Omega)$, or some problems in economics. In the continuous setting and assuming smoothness, the convexity constraints may be given locally by asking the Hessian matrix to be positive semidefinite, but in making discrete approximations two difficulties arise: the continuous solutions may be not smooth, and an adequate discrete version of the Hessian must be given. In this paper we propose a finite element description of the Hessian, and prove convergence under very general conditions, even when the continuous solution is not smooth, working on any dimension, and requiring a linear number of constraints in the number of nodes. Using semidefinite programming codes, we show concrete examples of approximations to optimization problems. TI - On convex functions and the finite element method KW - afriat-varian KW - algorithm KW - convex KW - discrete KW - semidefinite AU - Aguilera, Néstor AU - Morin, Pedro PY - 2008/Apr/10/ UR - http://arxiv.org/abs/0804.1780 ER -