Abstract

We organized a data mining challenge in “unsupervised and transfer learning” (the UTL challenge) followed by a workshop of the same name at the ICML 2011 conference in Bellevue, Washington. This introduction presents the highlights of the outstanding contributions that were made, which are regrouped in this issue of JMLR W&CP. Novel methodologies emerged to capitalize on large volumes of unlabeled data from tasks related (but different) from a target task, including a method to learn data kernels (similarity measures) and new deep architectures for feature learning.