Automata learning is a technique to infer an automaton model of a black-box system via
queries to the system. In recent years it has found widespread use both in industry and …

Recommender systems for software engineering (RSSEs) assist software engineers in
dealing with a growing information overload when discerning alternative development …

Recent advancements in machine learning and deep learning have brought algorithmic
fairness into sharp focus, illuminating concerns over discriminatory decision making that …

Electronic health record (EHR) datasets have increasingly been harnessed by artificial
intelligence (AI) for predictive modeling, yet the ethnicity fairness of these models remains …

The Machine learning widespread adoption has inadvertently led to the amplification of
societal biases and discrimination, with many consequential decisions now influenced by …

Multiple sclerosis (MS) is a complex, chronic, and heterogeneous disease of the central
nervous system that affects 3 million people globally. The multifactorial nature of MS …

Pre-trained Machine Learning (ML) models help to create ML-intensive systems without
having to spend conspicuous resources on training a new model from the ground up …

ML systems have become an essential tool for experts of many domains, data scientists and
researchers, allowing them to find answers to many complex business questions starting …

Fairness is a critical concept in ethics and social domains, but it is also a challenging
property to engineer in software systems. With the increasing use of machine learning in …

Generative models are nowadays widely used to generate graphical content used for
multiple purposes, eg web, art, advertisement. However, it has been shown that the images …