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    Combinatorial bounds on the α-divergence of univariate mixture models

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    Type
    Conference Paper
    Authors
    Nielsen, Frank
    Sun, Ke
    KAUST Department
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Date
    2017-06-20
    Online Publication Date
    2017-06-20
    Print Publication Date
    2017-03
    Permanent link to this record
    http://hdl.handle.net/10754/625623
    
    Metadata
    Show full item record
    Abstract
    We derive lower- and upper-bounds of α-divergence between univariate mixture models with components in the exponential family. Three pairs of bounds are presented in order with increasing quality and increasing computational cost. They are verified empirically through simulated Gaussian mixture models. The presented methodology generalizes to other divergence families relying on Hellinger-type integrals.
    Citation
    Nielsen F, Sun K (2017) Combinatorial bounds on the α-divergence of univariate mixture models. 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Available: http://dx.doi.org/10.1109/ICASSP.2017.7953003.
    Publisher
    Institute of Electrical and Electronics Engineers (IEEE)
    Journal
    2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
    Conference/Event name
    2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017
    DOI
    10.1109/ICASSP.2017.7953003
    Additional Links
    http://ieeexplore.ieee.org/document/7953003/
    ae974a485f413a2113503eed53cd6c53
    10.1109/ICASSP.2017.7953003
    Scopus Count
    Collections
    Conference Papers; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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