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...
The research in information extraction (IE) regards the generation of wrappers that can extract particular information from semistructured Web documents. Similar to compiler gener...
Abstract-- Despite of advances in machine learning technologies, a schema matching result between two database schemas (e.g., those derived from COMA++) is likely to be imprecise. ...
An ensemble of classifiers based algorithm, Learn++, was recently introduced that is capable of incrementally learning new information from datasets that consecutively become avail...
Michael Muhlbaier, Apostolos Topalis, Robi Polikar
Many approaches to learning classifiers for structured objects (e.g., shapes) use generative models in a Bayesian framework. However, state-of-the-art classifiers for vectorial d...