The motivation for this paper stems from the desire to develop an adaptive sampling method solving constrained optimization problems in which objective function is stochastic and constraints are deterministic. proposed a proximal gradient that can also be applied composite problem min f(x) + h(x), where f h convex (but not necessarily differentiable). Adaptive methods employ mechanism gradually...

Adaptive multigrid methods solve partial differential equations through a discrete representation of the domain that introduces more points in those zones where the equation behavior is highly irregular. The distribution of the points changes at run time in a way that cannot be foreseen in advance. We propose a methodology to develop a highly parallel solution based upon a load balancing strate...

Recently, adaptive wavelet strategies for symmetric, positive definite operators have been introduced that were proven to converge. This paper is devoted to the generalization to saddle point problems which are also symmetric, but indeenite. Firstly, we derive explicit criteria for adaptively reened wavelet spaces in order to fullll the Ladyshenskaja{Babu ska{Brezzi (LBB) condition and to be fu...

This paper provides a detailed comparison in solids mechanics context of adaptive mesh refinement methods for all-quadrilateral and all-hexahedral meshes. The multigrid Local Defect Correction method the well-known hierarchical h-adaptive techniques are placed into generic algorithmic setting an objective numerical comparison. Such is great interest as local AMR approaches from now rarely emplo...