http://ksem2018.venue.link/index.php?c=article&a=type&tid=60

The purpose of this track is to provide an extensive and intensive focus on transfer learning and knowledge reusing.

Transfer learning (TL) is motivated by the fact that people can intelligently apply knowledge learned previously to solve new problems faster and better. In contrast to classical machine learning methods, TL exploit the knowledge discovered from one or more auxiliary source domains to facilitate predictive modeling consisting of different data patterns in the target domain.

We encourage submissions on the following (non-exhaustive) list of topics:

• Transfer learning methods

• Applications of transfer learning

• Theory of knowledge reusability

• Explicable of transfer learning