Transfer learning (TL) is a technique in machine learning (ML) in which knowledge learned from a task is re-used in order to boost performance on a related...

Transfer of learning occurs when people apply information, strategies, and skills they have learned to a new situation or context. Transfer is not a discrete...

computational biology One-shot learning in computer vision Transfer learning Fast mapping Explanation-based learning Xian, Yongqin; Lampert, Christoph...

in the Science of Learning with additional material from the Committee on Learning Research (2000). Chapter 3. Learning and Transfer. How People Learn:...

generalization in learning. Routledge. Harris, S., Lowery-Moore, H., & Farrow, V. (2008). Extending Transfer of Learning Theory to Transformative Learning Theory:...

In behavioral psychology, negative transfer is the interference of the previous knowledge with new learning, where one set of events could hurt performance...

In statistics and machine learning, ensemble methods use multiple learning algorithms to obtain better predictive performance than could be obtained from...

Semi-supervised learning combines supervised and unsupervised learning, requiring only a small portion of the learning data be labeled. In transfer learning a model...

models, a process named transfer learning, to be used in psychiatry based on trained models from different fields. Transfer learning was used by researchers...

Reinforcement learning is one of three basic machine learning paradigms, alongside supervised learning and unsupervised learning. Reinforcement learning differs...