New privacy implications are induced to individuals and families because of the time-series
data classification problem in the Internet of Things such as appliance classifications in the …

We present a statistical mechanics theory of rubber-like elasticity in swollen and unswollen
polymer networks characterized by explicitly non-Gaussian distribution functions (Laplace's …

Using Stein's method techniques, we develop a framework which allows one to bound the
error terms arising from approximation by the Laplace distribution and apply it to the study of …

The variance-gamma (VG) distributions form a four-parameter family that includes as special
and limiting cases the normal, gamma and Laplace distributions. Some of the numerous …

Cross correlations are ubiquitous in time-series IoT data sets such as trajectories from
smartphones and smart meters data in smart grids. Conventional privacy methods have …

Temporally correlated trajectories are ubiquitous, and it has been a challenging problem to
protect the temporal correlation from being used against users' privacy. In this paper, we …

We use Stein's method to obtain explicit bounds on the rate of convergence for the Laplace
approximation of two different sums of independent random variables; one being a random …

With the widespread sharing of personal face images in applications' public databases, face
recognition systems faces real threat of being breached by potential adversaries who are …

We prove a transfer theorem for random sequences with independent random indexes in the
double array limit setting under relaxed conditions. We also prove its partial inverse …

A version of the central limit theorem is proved for sums with a random number of
independent and not necessarily identically distributed random variables in the double array …