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We present a randomized iterative algorithm that exponentially converges in the mean square to the minimum l(2)-norm least squares solution of a given linear system of equations. The expected number of arithmetic operations required to obtain an estimate o ...
Society for Industrial and Applied Mathematics2013
Biomaterials such as structure proteins are constructed from limited sets of chemical building blocks and supramolecular motifs. Nevertheless, they exhibit extraordinary properties specifically tailored for a broad range of applications because hierarchica ...
A comprehensive particle size distribution model has been developed for the simulation of gamma' precipitation in multicomponent Ni alloys. Nucleation, growth and coarsening of the precipitates are described by a particle size distribution. The growth rate ...
Gaussian belief propagation (GaBP) is an iterative algorithm for computing the mean (and variances) of a multivariate Gaussian distribution, or equivalently, the minimum of a multivariate positive definite quadratic function. Sufficient conditions, such as ...
Matrix factorization techniques such as the singular value decomposition (SVD) have had great success in recommender systems. We present a new perspective of SVD for constructing a latent space from the training data, which is justified by the theory of hy ...
A stable and efficient numerical scheme for the evaluation of surface integrals with 1/R-3-type singularities is presented. The method is based on the combination of the direct evaluation method and the singularity subtraction technique. The proposed metho ...
n this paper we present an architecture for an MMSE filter matrix computation unit for signal detection in MIMO-OFDM communication systems. We propose to compute the required matrix inverse based on a Cholesky decomposition, followed by a Gauss-Jordan matri ...
The matrix completion problem consists of finding or approximating a low-rank matrix based on a few samples of this matrix. We propose a new algorithm for matrix completion that minimizes the least-square distance on the sampling set over the Riemannian ma ...
We propose an algorithmic framework for convex minimization problems of a composite function with two terms: a self-concordant function and a possibly nonsmooth regularization term. Our method is a new proximal Newton algorithm that features a local quadra ...
An analytical formula for the shape derivative of the magnetic field integral equation (MFIE) method of moments (MoM) system matrix (or impedance matrix) is derived and validated against finite difference formulas. The motivation for computing the shape de ...
Institute of Electrical and Electronics Engineers2013
