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A General Compositional Operation in Random Process

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Title
A General Compositional Operation in Random Process
Author
Lee, Se-Hyun
Advisor
Kim, Kwang-In
Issue Date
2020-02
Publisher
Graduate School of UNIST
Abstract
We study general operation compositionality in a random process. It is known that the Gaussian process is closed under addition and multiplication assuming zero-mean, and it enables us to compose or decompose the kernel. This kind of property facilitates automated kernel search in the data space to find a more expressive kernel and build an accurate model. Although many other random processes are still used to research specific fields such as the Levy process in finance, the kernel selection for other processes except the Gaussian process remains heuristic. Therefore, we want to study the compositional operation in other random processes including the Gaussian process, Hawkes process, and Wiener process.
Description
Department of Computer Science and Engineering
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EE_Theses_Master
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