Training machine learning models on classical computers is usually a time and compute
intensive process. With Moore's law nearing its inevitable end and an ever-increasing …

Can dynamic ride-sharing reduce traffic congestion? In this paper we show that the answer
is yes if the trip density is high, which is usually the case in large-scale networks but not in …

Adiabatic quantum computers are a promising platform for efficiently solving challenging
optimization problems. Therefore, many are interested in using these computers to train …

Under the vision of industry 4.0, the integration of drones in last-mile delivery can transform
traditional delivery practices and provide competitive advantages. However, the …

In recent years, recommender systems have been used as a solution to support tourists with
recommendations oriented to maximize the entertainment value of visiting a tourist …

Entity resolution (ER) is a common data cleaning task that involves determining which
records from one or more data sets refer to the same real-world entities. Because a pairwise …

Drone small cells (DSCs) can provide on-demand air-to-ground wireless communications in
various unexpected situations, such as traffic jam or natural disasters. However, a DSC …

Traditional data mining methods for clustering only use unlabeled data objects as input. The
aim of such methods is to find a partition of these unlabeled data objects in order to discover …

Complex computations and analyses on massive data sets can be impractical or infeasible.
Data reduction is a crucial problem in the era of big data to obtain a reduced representation …

Licensed spectrum sharing has been a promised approach to provide mobile network
operators (MNOs) with required spectrum at times of increased traffic, or to improve the …