Whitening, or sphering, is a common preprocessing step in statistical analysis to transform
random variables to orthogonality. However, due to rotational freedom there are infinitely …

Orthogonal matrix has shown advantages in training Recurrent Neural Networks (RNNs),
but such matrix is limited to be square for the hidden-to-hidden transformation in RNNs. In …

Conventional wisdom suggests that parents' educational expectations (how far they expect
their children to go) and aspirations (how far they want their children to go) positively impact …

The rapid development of mobile technology has improved users' quality of treatment, and
tremendous amounts of medical information are readily available and widely used in data …

In this paper, we focus on differential privacy preserving spectral graph analysis. Spectral
graph analysis deals with the analysis of the spectra (eigenvalues and eigenvector …

This article explores four key questions about statistical models developed to describe the
recent past and future of vector-borne diseases, with special emphasis on dengue:(1) How …

Our study is among the first to provide a comprehensive review of cross-national patterns of
gender differences in various STEM-related constructs—achievement, beliefs, attitudes …

Whitening is a critical normalization method to enhance statistical reduction via
reparametrization to unit covariance. This article introduces the notion of whitening for …

We address the task of choosing prior weights for models that are to be used for weighted
model averaging. Models that are very similar should usually be given smaller weights than …

Quadratic forms capture multivariate information in a single number, making them useful, for
example, in hypothesis testing. When a quadratic form is large and hence interesting, it …