Multigrid computation of vector potentials

Multigrid for Eddy Current Computation

Algebraic multigrid support vector machines

The support vector machine is a flexible optimization-based technique widely used for classification problems. In practice, its training part becomes computationally expensive on large-scale data sets because of such reasons as the complexity and number of iterations in parameter fitting methods, underlying optimization solvers, and nonlinearity of kernels. We introduce a fast multilevel framew...

Local Computation with Gaussian Potentials

Gaussian or multivariate normal distributions are very popular and important probability models. Gaussian potentials [5] are multivariate normal density functions. Such a distribution is often given as a product of conditional Gaussian densities, which are more general than Gaussian potentials. These are related to Gaussian hints [11] and Gaussian belief functions [9, 10]. Gaussian potentials, ...

Rapid Computation of I-vector

I-vector has been one of the state-of-the-art techniques in speaker recognition. The main computational load of the standard i-vector extraction is to evaluate the posterior covariance matrix, which is required in estimating the i-vector. This limits the potential use of i-vector on handheld devices and for large-scale cloud-based applications. Previous fast approaches focus on simplifying the ...

Multigrid Accelerated Computation of Ligand-Receptor Interactions under Flow Condition

This paper describes a multigrid finite volume method developed to speed up the solution process for simulating complex biological transport phenomena. The method is applied to a model system which includes flow through a celllined cylindrical vessel and includes fibroblast growth factor-2 (FGF-2) within the fluid capable of binding to receptors and heparan sulfate proteoglycans (HSPGs) on the ...