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Filtering by: Keyword Gaussian process Keyword lifted Brownian random field Keyword variable selection Keyword variational inference Resource type Dissertation

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Several New Advances for Gaussian Process Models

Description:

Gaussian process provides a principled and flexible approach for modeling the response surface or the latent function in many areas, including machine learning, statistics and computer experiment. In literature, Gaussian process models have already demonstrated their effectiveness and usefulness in a variety of applications. In this dissertation, we mainly focus...

Keyword:

variable selection, variational inference, Gaussian process, and lifted Brownian random field

Subject:

Statistics

Creator:

Yu, Yang

Owner:

Scholarly Digital Publishing

Language:

en

Date Uploaded:

01/21/2021

Date Created:

2020-01-01

Resource Type:

Dissertation

Alternate Identifier:

http://dissertations.umi.com/northwestern:15098 and etdadmin_upload_742660

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Several New Advances for Gaussian Process Models

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