Description The Gaussian kernel is a popular choice for radial basis function approximation. For a fixed dimension, the error decays exponentially with sample size. However, the leading coefficient of...
Description In this talk we introduce a generalization of the classical L2(Rd)-based Sobolev spaces with the help of a vector operator P which consists of finitely or countably many operators Pn that...
Description We consider the problem of multivariate interpolation with radial basis functions consisting of a scaling parameter. In particular, we discuss the limit of interpolants by radial basis...
Description In computer experiments where each run is costly, one may wish to construct a surrogate, f (x) = Ψ T(x)β, that approximates the true response f : Ω → R. Here Ψ(x) =(Ψ1 (x), . . . , Ψk (x))...
Description First train a neural network in MATLAB with data (253 samples with 16 parameters each) provided by the company and give a brief experimental result analysis. Then based on this result...
Speaker Henryk Wozniakowski Columbia University http://www1.cs.columbia.edu/~henryk/ Description Multivariate problems occur in many applications. They are defined on spaces of d-variate functions and...
Description We study randomized algorithms for numerical integration with respect to a product probability measure on the sequence space $\R^\N$. We consider integrands from reproducing kernel Hilbert...
Description We use Taylor Expansion Method to solve the Nonlinear Stochastic Partial Equations with Random Boundary Conditions. As example, we studied the Nonlinear diffusion Equation (Ginzburg-Landau...
Event Topic: Computational Mathematics & Statistics
Description Current community models in the geosciences employ a variety of numerical methods from finite-difference, finite-volume, finite- or spectral elements, to pseudospectral methods. All have...
