To cope with concept drift, we paired a stable online learner with a reactive one. A stable learner predicts based on all of its experience, whereas a reactive learner predicts ba...
This paper presents the MicroNOMAD Discovering Tool. Its main characteristic is both to provide an user with emergent analyses of a multimedia database content and with querying a...
Jean-Charles Lamirel, Jacques Ducloy, Hager Kammou...
Rule induction research implicitly assumes that after producing the rules from a dataset, these rules will be used directly by an expert system or a human user. In real-life appli...
Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
Discovering association rules is one of the important tasks in data mining. While most of the existing algorithms are developed for efficient mining of frequent patterns, it has be...