Increases in the quantity of available data have allowed all fields of science to generate
more accurate models of multivariate phenomena. Regression and interpolation become …

Performance variability management is an active research area in high-performance
computing (HPC). In this article, we focus on input/output (I/O) variability, which is a …

Time-driven and access-driven attacks are two dominant types of the timing-based cache
side-channel attacks. Despite access-driven attacks are popular in recent years …

Performance variability is an important factor of high-performance computing (HPC)
systems. HPC performance variability is often complex because its sources interact and are …

Typical cybersecurity solutions emphasize on achieving defense functionalities. However,
execution efficiency and scalability are equally important, especially for real-world …

Large volumes of data allow for modern application of statistical and mathematical models to
practical social issues. Many applications of predictive models like criminal activity heat …

Although high-performance computing (HPC) systems have been scaled to meet the
exponentially-growing demand for scientific computing, HPC performance variability …

This thesis presents machine-learning based malware detection and post-detection
rewriting techniques for mobile and web security problems. In mobile malware detection, we …

This article presents several ways of managing input data from different perspectives and
the possibilities to use them on several interpolation methods and calibration techniques …

Function approximation is an important problem. This work presents applications of
interpolants to modeling random variables. Specifically, this work studies the prediction of …