We propose a probabilistic, generative account of configural learning phenomena in classical conditioning. Configural learning experiments probe how animals discriminate and gener...
Aaron C. Courville, Nathaniel D. Daw, David S. Tou...
Various problems in machine learning, databases, and statistics involve pairwise distances among a set of objects. It is often desirable for these distances to satisfy the propert...
Unsupervised learning algorithms have been derived for several statistical models of English grammar, but their computational complexity makes applying them to large data sets int...
The objective of our work is to provide some aid to the maintenance of a web site. The webmaster would like to get a semantic follow-up of the users’ browsing, but he only has a...
The development of FrameNet, a large database of semantically annotated sentences, has primed research into statistical methods for semantic tagging. We advance previous work by a...