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...

Learning is the process of acquiring new understanding, knowledge, behaviors, skills, values, attitudes, and preferences. The ability to learn is possessed...

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

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

research into the transfer and retrieval of prior learning. In his 1932 book Psychology of Study, C. A. Mace said: "On the matter of sheer repetitive drill...

the learning and use of a second language Transfer of learning, in education Transfer function in mathematics Transfer (group theory), a type of homomorphism...

specific application of the theory of transfer of learning that describes the positive, zero, or negative performance outcomes of a training program. The...

Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn...

use during the "information age", a family of terms – knowledge transfer, learning, transfer of learning, and knowledge sharing – are often used interchangeably...

therapy of the malignant brain tumours, localisation theory of the higher brain functions, hemispheric specialisation and interhemispheric transfer of learning...

learning is characterized "by a low degree of planning and organizing in terms of the learning context, learning support, learning time, and learning...

Organizational learning is the process of creating, retaining, and transferring knowledge within an organization. An organization improves over time as...

deep learning started impacting the field of art. Early examples included Google DeepDream (2015), and neural style transfer (2015), both of which were...

Federated learning (also known as collaborative learning) is a machine learning technique in a setting where multiple entities (often called clients)...

for "transfer of learning") is a historiographical concept which originated in the Middle Ages in which history is viewed as a linear succession of transfers...

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

retention of information and transfer of learning. Thalheimer conducted a meta-analysis that found, overall, a negative impact for the inclusion of seductive...

European Credit Transfer and Accumulation System (ECTS) is a standard means for comparing academic credits, i.e., the "volume of learning based on the defined...

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

Cooperative learning results in increased higher level reasoning and generation of new ideas and solutions, and greater transfer of learning between situations...

the rules of uncountable nouns. From a more general standpoint, Brown mentions "all new learning involves transfer based on previous learning". That could...

Some of the alternatives to rote learning include meaningful learning, associative learning, spaced repetition and active learning. Rote learning is widely...

"The influence of pattern similarity and transfer learning upon training of a base perceptron" (original in Croatian) Proceedings of Symposium Informatica...

(PDF) (MS Ed.). Dominican University of California. Solomon, Patricia (Summer 2015). Effect of Transfer of Learning of Jane Schaffer Writing Strategies on...

Experiential learning (ExL) is the process of learning through experience, and is more narrowly defined as "learning through reflection on doing". Hands-on...

for competence against a given set of standards or learning outcomes. RPL is sometimes confused with credit transfer, assessments conducted to recognize...

Multitask Learning is an approach to inductive transfer that improves generalization by using the domain information contained in the training signals of related...

adaptation is a field associated with machine learning and transfer learning. It addresses the challenge of training a model on one data distribution (the...

should aim for a balance of innovation and efficiency. This work is highly related to their theories of Transfer of Learning and research on instruction...