Abstract
In this paper, the different machine learning and data mining approaches used for Residential Energy Smart Management (RESM) will be discussed and classified according to some meaningful criteria. The proposed classification is an attempt to highlight the advantages and limitations of each category. Moreover, we emphasize the complementarity between approaches belonging to different categories and we point out the main challenges that still face RESM.