Lush is an object-oriented programming language designed for researchers, experimenters, and engineers interested in large-scale numerical and graphic applications.
MALLET is an integrated collection of Java code useful for statistical natural language processing, document classification, clustering, information extraction, and other machine learning applications to text.
The Standard ML project supports coordination between different implementations of the Standard ML (SML) programming language by maintaining common tools and resources such as standard test suites.
Neil Ireson, Fabio Ciravegna, Marie Elaine Califf, Dayne Freitag, Nicholas Kushmerick, Alberto Lavelli: Evaluating Machine Learning for Information Extraction, 22nd International Conference on Machine Learning (ICML 2005), Bonn, Germany, 7-11 August, 2005
This workshop is about how to design learning problems. The dominant system for applying machine learning in practice involves a human labeling data. This approach is limited to situations where human experts exist, can be afforded, and are fast enough to solve the relevant problem.
M. Mladenov, L. Kleinhans, and K. Kersting. Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI), (2017)Preprint available at https://arxiv.org/abs/1606.04486.
D. Koller, and A. Pfeffer. Proceedings of the 13th Annual Conference on Uncertainty in AI (UAI), page 302--313. (1997)Winner of the Best Student Paper Award.