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.
|Original language||English (US)|
|Title of host publication||2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)|
|Publisher||Institute of Electrical and Electronics Engineers (IEEE)|
|Number of pages||5|
|State||Published - Jun 20 2017|