Measure of Similarity between GMMs Based on Autoencoder-Generated Gaussian Component Representations
Vladimir Kalušev,
Branislav Popović,
Marko Janev
et al.
Abstract:A novel similarity measure between Gaussian mixture models (GMMs), based on similarities between the low-dimensional representations of individual GMM components and obtained using deep autoencoder architectures, is proposed in this paper. Two different approaches built upon these architectures are explored and utilized to obtain low-dimensional representations of Gaussian components in GMMs. The first approach relies on a classical autoencoder, utilizing the Euclidean norm cost function. Vectorized upper-diag… Show more
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