Artificial intelligence (AI) has emerged as a powerful tool that harnesses anthropomorphic
knowledge and provides expedited solutions to complex challenges. Remarkable …

Industry 4.0 is the new industrial revolution. By connecting every machine and activity
through network sensors to the Internet, a huge amount of data is generated. Machine …

The complexity and dynamics of the environment make it extremely difficult to directly predict
and trace the temporal and spatial changes in pollution. In the past decade, the …

Abstract Machine learning is a branch of computer science that has the potential to transform
epidemiologic sciences. Amid a growing focus on “Big Data,” it offers epidemiologists new …

Propensity score matching (PSM) is a popular method in clinical researches to create a
balanced covariate distribution between treated and untreated groups. However, the …

The interdisciplinary field of knowledge discovery and data mining emerged from a
necessity of big data requiring new analytical methods beyond the traditional statistical …

It is increasingly important to accurately and comprehensively estimate the effects of
particular clinical treatments. Although randomization is the current gold standard …

We study deep neural networks and their use in semiparametric inference. We establish
novel nonasymptotic high probability bounds for deep feedforward neural nets. These …

Deep learning takes advantage of large datasets and computationally efficient training
algorithms to outperform other approaches at various machine learning tasks. However …

Many scientific and engineering challenges—ranging from personalized medicine to
customized marketing recommendations—require an understanding of treatment effect …