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From convex feasibility to convex constrained optimization using block action projection methods and underrelaxation
(Wiley-blackwellMaldenEUA, 2009)
Lower-semicontinuity and optimization of convex functionals
(2009-12-01)
The result that we treat in this article allows to the utilization of classic tools of convex analysis in the study of optimality conditions in the optimal control convex process for a Volterra-Stietjes linear integral ...
Lower-semicontinuity and optimization of convex functionals
(2009-12-01)
The result that we treat in this article allows to the utilization of classic tools of convex analysis in the study of optimality conditions in the optimal control convex process for a Volterra-Stietjes linear integral ...
On Convex Functions and the Finite Element Method
(Society for Industrial and Applied Mathematics, 2009-12)
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 ...
A convex analysis approach for convex multiplicative programming
(SpringerDordrechtHolanda, 2008)
Subdifferential of the Supremum via Compactification of the Index Set
(Springer, 2020)
We give new characterizations for the subdifferential of the supremum of an arbitrary family of convex functions, dropping out the standard assumptions of compactness of the index set and upper semi-continuity of the ...
Weaker conditions for subdifferential calculus of convex functions
(Elsevier, 2016)
In this paper we establish new rules for the calculus of the subdifferential mapping of the sum of two convex functions. Our results are established under conditions which are at an intermediate level of generality among ...
Sufficient Optimality Conditions for Optimal Control Problems with State Constraints
(2019-06-11)
It is well-known in optimal control theory that the maximum principle, in general, furnishes only necessary optimality conditions for an admissible process to be an optimal one. It is also well-known that if a process ...
On variance reduction for stochastic smooth convex optimization with multiplicative noise
(Springer Verlag, 2019)
© 2018, Springer-Verlag GmbH Germany, part of Springer Nature and Mathematical Optimization Society. We propose dynamic sampled stochastic approximation (SA) methods for stochastic optimization with a heavy-tailed distribution ...