Abstract:
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In this talk, we consider cluster analysis of high-dimensional tensor Gaussian mixtures. We will present some recent work on probabilistic mixture models involving tensor data where the cluster analysis can be substantially improved by projecting the data onto latent low-dimensional subspace and/or by feature selection on tensors.
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