Guillaume Rabusseau

Guillaume’s work focuses on tensor methods for machine learning and in designing learning algorithms for structured data by leveraging linear and multilinear algebra (e.g. spectral methods). An Assistant Professor at Mila and in the Department of Computer Science and Operations Research (DIRO) at Université de Montréal, Guillaume’s research interests lie at the intersection of theoretical computer science and machine learning.