Feature selection (FS) is commonly thought of as a pre-processing strategy for determining
the best subset of characteristics from a given collection of features. Here, a novel discrete …

Graph signal processing has recently emerged as a field with applications across a broad
spectrum of fields including brain connectivity networks, logistics and supply chains, social …

Tensor algebra is the next evolutionary step of linear algebra to more than two dimensions.
Its plethora of applications include signal processing, big data, deep learning, multivariate …

Startups arguably contribute to the current business landscape by developing innovative
products and services. The discovery of business partners and employees with a specific …

In communication networks resilience or structural coherency, namely the ability to maintain
total connectivity even after some data links are lost for an indefinite time, is a major design …

Self organizing maps (SOMs) are neural networks designed to be in an unsupervised way to
create connections, learned through a modified Hebbian rule, between a high-(the input …

In the current paper, we propose a machine learning forecasting model for the accurate
prediction of qualitative weather information on winter precipitation types, utilized in Apache …

Computer games play an increasingly important role in cultural heritage preservation. They
keep tradition alive in the digital domain, reflect public perception about historical events …

At the dawn of the 10V or big data data era, there are a considerable number of sources
such as smart phones, IoT devices, social media, smart city sensors, as well as the health …

Substantial empirical evidence, including the success of synthetic graph generation models
as well as of analytical methodologies, suggests that large, real graphs have a recursive …