This paper presents some linear adaptive non-nested multigrid methods which are applied to linear elastic problems discretized with triangular and tetrahedral nite elements using unstructured and Delaunay mesh generators. The Zienkiewicz-Zhu error estimator and a h-re nement procedure are used to obtain the non-nested meshes used by the multigrid methods. We solve problems with a speci ed perce...

This paper presents a method for adaptation in Metropolis-Hastings algorithms. A product of a proposal density and K copies of the target density is used to define a joint density which is sampled by a Gibbs sampler including a Metropolis step. This provides a framework for adaptation since the current value of all K copies of the target distribution can be used in the proposal distribution. Th...

We study a class of overrelaxed bound optimization algorithms, and their relationship to standard bound optimizers, such as ExpectationMaximization, Iterative Scaling, CCCP and Non-Negative Matrix Factorization. We provide a theoretical analysis of the convergence properties of these optimizers and identify analytic conditions under which they are expected to outperform the standard versions. B...

We propose a new adaptive spatio-temporal interpolation method that combines either by a step or a line function existing spatial and temporal interpolation methods. We test the new method using climate data obtained from weather stations in Colorado and Nebraska, for the time period from 1993 to 2003. The experimental results show that in mountainous regions our adaptive spatio-temporal method...

The task of approximating a non linear mapping using a limited number of observations, asks the data analyst to make several choices involving the set of relevant variables and observations, the learning algorithm, and the validation protocol. In the case of models which are linear in the parameters (e.g. polynomials), statistical theory and economical cross-validat ion met hods provide fast an...