In simulation-based realization of complex systems, we are forced to address the issue of
computational complexity. One critical issue that must be addressed is the approximation of …

Big multimedia data is heterogeneous in essence, that is, the data may be a mixture of
video, audio, text, and images. This is due to the prevalence of novel applications in recent …

Dealing with imbalanced data is a prevalent problem while performing classification on the
datasets. Many times, this problem contributes to bias while making decisions or …

Online social media drive the growth of unstructured text data. Many marketing applications
require structuring this data at scales non-accessible to human coding, eg, to detect …

Financial statement fraud is an area of significant consternation for potential investors,
auditing companies, and state regulators. The paper proposes an approach for detecting …

This paper provides a review and commentary on the past, present, and future of numerical
optimization algorithms in the context of machine learning applications. Through case …

The extraction of useful insights from text with various types of statistical algorithms is
referred to as text mining, text analytics, or machine learning from text. The choice of …

In this paper, we document basic facts regarding public debates about controversial political
issues on Chinese social media. Our documentation is based on a dataset of 13.2 billion …

With the utilization of deep learning approaches, the key factors for a successful application
are sufficient datasets with reliable ground truth, which are generally not easy to obtain …

The problem of classification has been widely studied in the data mining, machine learning,
database, and information retrieval communities with applications in a number of diverse …