Adeline Fermanian




We will be concerned with the application of signatures to machine learning and statistics. The basic principle of the signature method is to represent multidimensional paths by a graded feature set of their iterated integrals, called the signature. After a general overview of signatures in machine learning, we will focus on two specific problems: estimation in a linear regression setting and building a canonical signature pipeline for time series classification.