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Thesis

Rough paths, kernels, differential equations and an algebra of functions on streams

Abstract:

This thesis is organised in the following four chapters. Appendix A provides asummary of rough path theory.

Chapter 1: Recently, there has been an increased interest in the development of kernel methods for learning with sequential data.The signature kernel is a learning tool with potential to handle irregularly sampled, multivariate time series. In [1] the authors introduced a kernel trick for the truncated version of this kernel avoiding the exponential complexity thatwould have ...

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Division:
MPLS
Department:
Mathematical Institute
Role:
Author

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Role:
Supervisor
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
University of Oxford

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