-of-the-art learning algorithms in this setting. Finally, we note that this sample selection issue is prevalent not only on crowdsourcing …

applying machine learning because of changes in the probability distribution (features or labels) between the training and test … data as well as lack of recent training examples. Transfer learning is a technique that performs well despite these … problems. We have applied a transfer learning-based approach to detect the unknown ransomware malware families. In particular …

Physicists have had a keen interest in the areas of Artificial Intelligence (AI) and Machine Learning (ML) for some … time now, with a special inclination towards unravelling the mechanism at the core of the process of learning. In … the epistemological meaning of ‘Learning’ but also has the potential to unravel the secrets behind the workings of the …

role of learning and knowledge in energy transitions in general and CECs’ knowledge circulation and learning processes in … particular. The paper presents findings about the knowledge development and learning processes within CECs, ways of cultivating …. This research contributes to the energy transition literature by focusing on the overlooked perspective of learning and …

, and non-monotonically, on the expected return on the risky activity, leading to three learning regimes including a …

Millions Learning, a project of the Center for Universal Education (CUE) at the Brookings Institution, addresses the …