Inductive transfer
Encyclopedia
Inductive transfer, or transfer learning, is a research problem in machine learning
that focuses on storing knowledge gained while solving one problem and applying it to a different but related problem. For example, the abilities acquired while learning to walk presumably apply when one learns to run, and knowledge gained while learning to recognize cars could apply when recognizing trucks. This area of research bears some relation to the long history of psychological literature on transfer of learning
, although formal ties between the two fields are limited.
Notably, scientists have developed algorithms for inductive transfer in Markov logic network
s and Bayesian networks. Furthermore, researchers have applied techniques for transfer to problems in text classification
, spam filtering
, and urban combat simulation.
There still exists much potential in this field while the "transfer" hasn't yet led to significant improvement in learning. Also, an intuitive understanding could be that "transfer means a learner can directly learn from other correlated learners". However, in this way, such a methodology in transfer learning, whose direction is illustrated by, is not a hot spot in the area yet.
Machine learning
Machine learning, a branch of artificial intelligence, is a scientific discipline concerned with the design and development of algorithms that allow computers to evolve behaviors based on empirical data, such as from sensor data or databases...
that focuses on storing knowledge gained while solving one problem and applying it to a different but related problem. For example, the abilities acquired while learning to walk presumably apply when one learns to run, and knowledge gained while learning to recognize cars could apply when recognizing trucks. This area of research bears some relation to the long history of psychological literature on transfer of learning
Transfer of learning
Transfer of learning is the study of the dependency of human conduct, learning, or performance on prior experience. The notion was originally introduced as transfer of practice by Edward Thorndike and Robert S. Woodworth...
, although formal ties between the two fields are limited.
Notably, scientists have developed algorithms for inductive transfer in Markov logic network
Markov logic network
A Markov logic network is a probabilistic logic which applies the ideas of a Markov network to first-order logic, enabling uncertain inference...
s and Bayesian networks. Furthermore, researchers have applied techniques for transfer to problems in text classification
Document classification
Document classification or document categorization is a problem in both library science, information science and computer science. The task is to assign a document to one or more classes or categories. This may be done "manually" or algorithmically...
, spam filtering
E-mail filtering
Email filtering is the processing of email to organize it according to specified criteria. Most often this refers to the automatic processing of incoming messages, but the term also applies to the intervention of human intelligence in addition to anti-spam techniques, and to outgoing emails as well...
, and urban combat simulation.
There still exists much potential in this field while the "transfer" hasn't yet led to significant improvement in learning. Also, an intuitive understanding could be that "transfer means a learner can directly learn from other correlated learners". However, in this way, such a methodology in transfer learning, whose direction is illustrated by, is not a hot spot in the area yet.