This paper presents an active learning approach to the problem of systematic noise inference and noise elimination, specifically the inference of Associated Corruption (AC) rules...
—This research aims to enable robots to learn from human teachers. Motivated by human social learning, we believe that a transparent learning process can help guide the human tea...
In the context of large databases, data preparation takes a greater importance : instances and explanatory attributes have to be carefully selected. In supervised learning, instanc...
Abstract—We propose a probabilistic model for analyzing spatial activation patterns in multiple functional magnetic resonance imaging (fMRI) activation images such as repeated ob...
In the inductive inference framework of learning in the limit, a variation of the bounded example memory (Bem) language learning model is considered. Intuitively, the new model con...