Machine learning heavily relies on data, but real-world applications often encounter various
data-related issues. These include data of poor quality, insufficient data points leading to …

An increasing number of decisions regarding the daily lives of human beings are being
controlled by artificial intelligence and machine learning (ML) algorithms in spheres ranging …

This article provides a comprehensive survey of bias mitigation methods for achieving
fairness in Machine Learning (ML) models. We collect a total of 341 publications concerning …

Generative Adversarial Networks (GANs) is a novel class of deep generative models that
has recently gained significant attention. GANs learn complex and high-dimensional …

An increasing number of decisions regarding the daily lives of human beings are being
controlled by artificial intelligence (AI) and machine learning (ML) algorithms in spheres …

There are increasing concerns about the bias and fairness of artificial intelligence (AI)
models as they are put into clinical practice. Among the steps for implementing machine …

Artificial Intelligence (AI) has become an important component of many software
applications. It has reached a point where it can provide complex and critical decisions in …

The recent adoption of machine learning models in high-risk settings such as medicine has
increased demand for developments in privacy and fairness. Rebalancing skewed datasets …

The You Only Look Once (YOLO) series, renowned for its efficiency and versatility in object
detection, has become a fundamental component in diverse fields ranging from autonomous …

The increasing use of machine learning in learning analytics (LA) has raised significant
concerns around algorithmic fairness and privacy. Synthetic data has emerged as a dual …