In last two decades, various monitoring systems have been designed and deployed in urban
environments, toward the realization of the so called smart cities. Such systems are based …

\emphCoresets are compact representations of data sets such that models trained on a
coreset are provably competitive with models trained on the full data set. As such, they have …

How can we train a statistical mixture model on a massive data set? In this work we show
how to construct coresets for mixtures of Gaussians. A coreset is a weighted subset of the …

For the health and safety of the public, it is essential to measure spatiotemporal distribution
of air pollution in a region and thus monitor air quality in a fine-grain manner. While most of …

This paper proposes a nonmodel-based framework for estimating story-based engineering
demand parameters (EDPs) in instrumented steel frame buildings with steel moment …

Network application optimization is essential for improving the performance of the
application as well as its user experience. The network application parameters are crucial in …

Modern stochastic optimization methods often rely on uniform sampling which is agnostic to
the underlying characteristics of the data. This might degrade the convergence by yielding …

With advances in technology and an increasing variety of inexpensive geosensors,
environmental monitoring has become increasingly sensor dense and real time. Using …

Accelerometers are used in a wide variety of applications including inertial navigation
systems and activity monitors. In order to reduce systematic and random errors and improve …

Our current society is facing challenges in both sustainability and environmental pollution
due to fast urbanization, limited resources, and increasing senior population. Smart cities …