Artificial intelligence techniques have grown rapidly in recent years, and their applications in
practice can be seen in many fields, ranging from facial recognition to image analysis. In the …

In recent years, self-attention has become the dominant paradigm for sequence modeling in
a variety of domains. However, in domains with very long sequence lengths the $\mathcal …

Background Low-complexity data analysis is the area that addresses the search and
quantification of regions in sequences of elements that contain low-complexity or repetitive …

Being able to experience emotions is a defining characteristic of machine intelligence, and
the first step in giving robots emotions is to enable them to accurately recognize and …

Nowadays, information and communications technology systems are fundamental assets of
our social and economical model, and thus they should be properly protected against the …

The increasing level of sophistication of cyber attacks which are employing cross-cutting
strategies that leverage multi-domain attack surfaces, including but not limited to, software …

Compression analytics have gained recent interest for application in malware classification
and digital forensics. This interest is due to the fact that compression analytics rely on …

It is generally well understood that predictive classification and compression are intrinsically
related concepts in information theory. Indeed, many deep learning methods are explained …

This paper introduces a novel complexity-informed approach to cybersecurity management,
addressing the challenges found within complex cyber defences. We adapt and extend the …

Anomaly detection refers to the problem of identifying abnormal behaviour within a set of
measurements. In many cases, one has some statistical model for normal data, and wishes …