Preprint 78/2018

Learning Paths from Signature Tensors

Max Pfeffer, Anna Seigal, and Bernd Sturmfels

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Submission date: 10. Sep. 2018
Pages: 28
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Abstract:
Matrix congruence extends naturally to the setting of tensors. We apply methods from tensor decomposition, algebraic geometry and numerical optimization to this group action. Given a tensor in the orbit of another tensor, we compute a matrix which transforms one to the other. Our primary application is an inverse problem from stochastic analysis: the recovery of paths from their signature tensors of order three. We establish identifiability results and recovery algorithms for piecewise linear paths, polynomial paths, and generic dictionaries. A detailed analysis of the relevant condition numbers is presented. We also compute the shortest path with a given signature tensor.

13.09.2018, 00:13