Recent advances in artificial intelligence (AI) have led to its widespread industrial adoption,
with machine learning systems demonstrating superhuman performance in a significant …

The communication and networking field is hungry for machine learning decision-making
solutions to replace the traditional model-driven approaches that proved to be not rich …

Artificial intelligence (AI) is currently being utilized in a wide range of sophisticated
applications, but the outcomes of many AI models are challenging to comprehend and trust …

Although anaesthesiologists strive to avoid hypoxaemia during surgery, reliably predicting
future intraoperative hypoxaemia is not possible at present. Here, we report the …

This paper provides a framework for addressing the question of when transactions should
be carried out within a firm and when through the market. Following Grossman and Hart, we …

Abstract Background and Objective When using machine learning techniques in decision-
making processes, the interpretability of the models is important. In the present paper, we …

Boolean functions are perhaps the most basic objects of study in theoretical computer
science. They also arise in other areas of mathematics, including combinatorics, statistical …

The Shapley value has become popular in the Explainable AI (XAI) literature, thanks, to a
large extent, to a solid theoretical foundation, including four “favourable and fair” axioms for …

As image-based deep learning becomes pervasive on every device, from cell phones to
smart watches, there is a growing need to develop methods that continually learn from data …

Tree-based machine learning models such as random forests, decision trees, and gradient
boosted trees are the most popular non-linear predictive models used in practice today, yet …