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    • Mixture Density Mercer Kernels: A Method to Learn Kernels

    Metadata Updated: December 6, 2023

    This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture density estimate. We show how to convert the ensemble estimates into a Mercer Kernel, describe the properties of this new kernel function, and give examples of the performance of this kernel on unsupervised clustering of synthetic data and also in the domain of unsupervised multispectral image understanding.

    Access & Use Information

    Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

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    Dates

    Metadata Created Date November 12, 2020
    Metadata Updated Date December 6, 2023
    Data Update Frequency irregular

    Metadata Source

    Harvested from NASA Data.json

    Other Data Resources

    Additional Metadata

    Resource Type Dataset
    Metadata Created Date November 12, 2020
    Metadata Updated Date December 6, 2023
    Publisher Dashlink
    Maintainer
    Identifier DASHLINK_157
    Data First Published 2010-09-22
    Data Last Modified 2020-01-29
    Public Access Level public
    Data Update Frequency irregular
    Bureau Code 026:00
    Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
    Metadata Catalog ID https://data.nasa.gov/data.json
    Schema Version https://project-open-data.cio.gov/v1.1/schema
    Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
    Harvest Object Id e55ef031-2c56-4bda-b6ff-274ef3548a6f
    Harvest Source Id 58f92550-7a01-4f00-b1b2-8dc953bd598f
    Harvest Source Title NASA Data.json
    Homepage URL https://c3.nasa.gov/dashlink/resources/157/
    Program Code 026:029
    Source Datajson Identifier True
    Source Hash ce2ffa8c46226286273d16cf6c7fcb2f138e9358feff2ba945f82afe93e35899
    Source Schema Version 1.1

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