The mission of the Journal of Machine Learning Gossip (JMLG) is to provide an archival source of important information that is often discussed informally at conferences but is rarely, if ever, written down.
The Knowledge Discovery Machine Learning (KDML) group focuses on the neighboring subfields of computer science known as knowledge discovery in databases (KDD, sometimes referred to simply as data mining) and machine learning (ML). For us, these fields include on the one hand the automated analysis of large data sets using intelligent algorithms that are capable of extracting from the collected data hidden knowledge in order to produce models that can be used for prediction and decision making. On the other hand, they also include algorithms and systems that are capable of learning from experience and adapting to their environment or their users.
R. Kohavi. Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, стр. 1137-1145. San Mateo, CA: Morgan Kaufmann, (1995)
D. Nguyen, N. Smith, и C. Rosé. Proceedings of the 5th ACL-HLT Workshop on Language Technology for Cultural Heritage, Social Sciences, and Humanities, стр. 115--123. Stroudsburg, PA, USA, Association for Computational Linguistics, (2011)