Parsimonious Representations in data science – Dr Armin Eftekhari, University of Edinburgh

Every minute, humankind produces about 2000 Terabytes of data and learning from this data has the potential to improve many aspects of our lives. Doing so requires exploiting the geometric structure hidden within the data. Our overview of models in data and computational sciences starts with the ubiquitous linear subspace model. As an example, we will study the band-limited model that enabled the digital revolution. We will also review the principal component analysis, as the main statistical tool for learning linear structure in collected data.