In Proceedings of ICML ' 96 : The 13 th International Conference on Machine Learning

Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29 - July 2, 2000

Machine Learning, Proceedings of the Nineteenth International Conference (ICML 2002), University of New South Wales, Sydney, Australia, July 8-12, 2002

In the Proceedings of the 15 th International Conference on Machine Learning ( ICML - 98 ) Well - Behaved

How can we guarantee that our software and robotic agents will behave as we require, even after learning? Formal veri cation should play a key role but can be computationally expensive, particularly if re-veri cation follows each instance of learning. This is especially a problem if the agents need to make rapid decisions and learn quickly while online. Therefore, this paper presents novel meth...

In Proceedings of the ICML Workshop on Structural Knowledge Transfer for Machine Learning . Pittsburgh , PA , July 2006 . Transfer Learning with Markov

Joint Transfer and Batch-mode Active Learning

Active learning and transfer learning are two different methodologies that address the common problem of insufficient labels. Transfer learning addresses this problem by using the knowledge gained from a related and already labeled data source, whereas active learning focuses on selecting a small set of informative samples for manual annotation. Recently, there has been much interest in develop...