Due to the scarcity of well labeled epileptic seizure data and the usual rarity of seizure events of an average patient, it becomes relevant to develop methods capable of using data from multiple patients aiming at improving classification performance on a specific patient. With this purpose in mind, we propose a method that uses a multi-objective optimization method to share data and learning parameters from a source patient to a target patient.