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...
In this paper we propose a method for grouping and summarizing large sets of association rules according to the items contained in each rule. We use hierarchical clustering to par...
In this paper, we address the problem of robustly recovering several instances of a curve model from a single noisy data set with outliers. Using M-estimators revisited in a Lagran...
Jean-Philippe Tarel, Pierre Charbonnier, Sio-Song ...
Mining Meets Abstract Interpretation J. Carmona and J. Cortadella Universitat Polit`ecnica de Catalunya, Spain The discovery of process models out of system traces is a problem tha...
In ubiquitous computing, behavior routine learning is the process of mining the context-aware data to find interesting rules on the user’s behavior, while preference learning tri...