Representation learning and Deep learning

Representation learning emerged over the last ten years at the confluence of different domains with the aim of learning meaningful representations from data. The flagship today is represented by Deep Neural Networks. MLIA has a strong historical position on this domain and a large part of its research is within this field. Over this period, we have investigated learning representation for structured and dynamic data, with applications in Computer Vision, Natural Language Processing, Social Data Analysis and Recommendation.