Parameter Tuning Using Gaussian Processes
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Parameter Tuning Using Gaussian Processes
Summary
Parameter Tuning Using Gaussian Processes is a master's thesis[1].
Key Facts
- Parameter Tuning Using Gaussian Processes's instance of is recorded as master's thesis[2].
- Parameter Tuning Using Gaussian Processes was published by Waikato Research Commons[3].
- Parameter Tuning Using Gaussian Processes's place of publication is recorded as Hamilton[4].
- Parameter Tuning Using Gaussian Processes's language of work or name is recorded as English[5].
- Parameter Tuning Using Gaussian Processes's country of origin is recorded as New Zealand[6].
- Parameter Tuning Using Gaussian Processes was released on 2012[7].
- Parameter Tuning Using Gaussian Processes's main subject is machine learning[8].
- Parameter Tuning Using Gaussian Processes's work available at URL is recorded as https://researchcommons.waikato.ac.nz/handle/10289/6497[9].
- Parameter Tuning Using Gaussian Processes's title is recorded as Parameter Tuning Using Gaussian Processes[10].
- Parameter Tuning Using Gaussian Processes's author name string is recorded as Jinjin Ma[11].
- Parameter Tuning Using Gaussian Processes's thesis submitted to is recorded as University of Waikato[12].
- Parameter Tuning Using Gaussian Processes's on focus list of Wikimedia project is recorded as NZThesisProject[13].
- Parameter Tuning Using Gaussian Processes's copyright status is recorded as copyrighted[14].
- Parameter Tuning Using Gaussian Processes's online access status is recorded as open access[15].
- Parameter Tuning Using Gaussian Processes's thesis committee member is recorded as Eibe Frank[16].
- Parameter Tuning Using Gaussian Processes's thesis committee member is recorded as Geoffrey Holmes[17].
- Parameter Tuning Using Gaussian Processes's thesis submitted for degree is recorded as Master of Science[18].
Body
Designation and Status
Parameter Tuning Using Gaussian Processes's instance of is recorded as master's thesis[2].