Invention Grant
- Patent Title: Data driven evaluation and rejection of trained Gaussian process-based wireless mean and standard deviation models
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Application No.: US14843955Application Date: 2015-09-02
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Publication No.: US09838847B2Publication Date: 2017-12-05
- Inventor: Brian John Julian , Etienne Le Grand , Brian Patrick Williams
- Applicant: Google Inc.
- Applicant Address: US CA Mountain View
- Assignee: Google LLP
- Current Assignee: Google LLP
- Current Assignee Address: US CA Mountain View
- Agency: McDonnell Boehnen Hulbert & Berghoff LLP
- Main IPC: H04W4/02
- IPC: H04W4/02 ; H04L12/24 ; H04L12/26

Abstract:
Disclosed are apparatus and methods for providing outputs; e.g., location estimates, based on trained Gaussian processes. A computing device can determine trained Gaussian processes related to wireless network signal strengths, where a particular trained Gaussian process is associated with one or more hyperparameters. The computing device can designate one or more hyperparameters. The computing device can determine a hyperparameter histogram for values of the designated hyperparameters of the trained Gaussian processes. The computing device can determine a candidate Gaussian process associated with one or more candidate hyperparameter value for the designated hyperparameters. The computing device can determine whether the candidate hyperparameter values are valid based on the hyperparameter histogram. The computing device can, after determining that the candidate hyperparameter values are valid, add the candidate Gaussian process to the trained Gaussian processes. The computing device can provide an estimated location output based on the trained Gaussian processes.
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