Abstract: With the prevalence of machine learning in many high-stakes decision-making processes, e.g., hiring and admission, it is important to take fairness into account when practitioners design and ...

Continual robot learning is an emerging interdisciplinary field that integrates advances from machine learning, robotics, and cognitive science to build ...

Across Africa, a new generation of policy oriented technologists is beginning to redefine the relationship between governance, economic development, clean energy transition, and Artificial ...

Computer scientists urge a fundamental shift in how problems are formulated in reinforcement learning for healthcare ...

Abstract: Recently, Optimal Transport has been proposed as a probabilistic framework in Machine Learning for comparing and manipulating probability distributions. This is rooted in its rich history ...

The field of machine learning is traditionally divided into two main categories: "supervised" and "unsupervised" learning. In supervised learning, algorithms are trained on labeled data, where each ...