It has been shown that dimension reduction methods such as Principal Component Analysis
(PCA) may be inherently prone to unfairness and treat data from different sensitive groups …

As algorithmic decision-making systems are becoming more pervasive, it is crucial to ensure
such systems do not become mechanisms of unfair discrimination on the basis of gender …

Due to biases introduced by large real-world datasets, deviations of deep learning models
from their expected behavior on out-of-distribution test data are worrisome. Especially when …

Abstract Application Programming Interface (API) recommendation based on graphs is a
valuable task in the fields of data visualization and software engineering. However, this task …

Meta-learning in the broader context concerns how an agent learns about their own
learning, allowing them to improve their learning process. Learning how to learn is not only …

Machine learning applications are challenged by data difficulty factors, which are
responsible for the degradation of data quality and dealing with them is a demanding task …

Achieving astounding progress and evolution during the past few decades, Artificial
Intelligence (AI) is becoming omnipresent in every aspect of our lives. Nowadays, AI systems …

Abstract Application Programming Interface (API) recommendation based on graphs is a
meaningful task in the context of software engineering and data visualization. However, this …

Abstract Machine learning applications are challenged by data difficulty factors, which are
responsible for the degradation of data quality and dealing with them is a demanding task …