Transfer learning can be described as the tion of abstract knowledge from one learning domain or task and the reuse of that knowledge in a related domain or task. In categorizatio...
Kevin R. Canini, Mikhail M. Shashkov, Thomas L. Gr...
Knowledge Discovery in Databases (KDD) has become a very attractive discipline both for research and industry within last few years. Its goal is to extract pieces of knowledge or `...
Since its birth, more than five decades ago, one of the biggest challenges of artificial intelligence remained the building of intelligent machines. Despite amazing advancements, ...
This paper promotes the use of supervised machine learning in laboratory settings where chemists have a large number of samples to test for some property, and are interested in id...
We study the problem of automatically discovering semantic associations between schema elements, namely foreign keys. This problem is important in all applications where data sets...
Alexandra Rostin, Oliver Albrecht, Jana Bauckmann,...