This is a preview. Log in through your library . Publisher Information "The Society for Industrial and Applied Mathematics is a leading international association for applied mathematics, and its ...

Eigenvalue problems are a cornerstone of modern applied mathematics, arising in diverse fields from quantum mechanics to structural engineering. At their heart, these problems seek scalar values and ...

This is a preview. Log in through your library . Abstract We consider a multivariate heavy-tailed stochastic volatility model and analyze the large-sample behavior of its sample covariance matrix. We ...

Now assume to be symmetric with non-zero off-diagonal elements, i.e. , . Let be the eigenvalues and the normalized eigenvectors of T, i.e. We consider the inverse problem: Determine from and . It is ...

Network analysis begins with data that describes the set of relationships among the members of a system. The goal of analysis is to obtain from the low-level relational data a higher-level description ...

Transforming a dataset into one with fewer columns is more complicated than it might seem, explains Dr. James McCaffrey of Microsoft Research in this full-code, step-by-step machine learning tutorial.

Correction: The original version of this article incorrectly stated that eigenvalues are the magnitudes of eigenvectors. In fact, eigenvalues are scalars that are multiplied with eigenvectors. This ...