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The variational hierarchical EM algorithm for clustering hidden Markov models.
Emanuele Coviello · Antoni Chan · Gert Lanckriet

Wed Dec 05 07:00 PM -- 12:00 AM (PST) @ Harrah’s Special Events Center 2nd Floor

In this paper, we derive a novel algorithm to cluster hidden Markov models (HMMs) according to their probability distributions. We propose a variational hierarchical EM algorithm that i) clusters a given collection of HMMs into groups of HMMs that are similar, in terms of the distributions they represent, and ii) characterizes each group by a ``cluster center'', i.e., a novel HMM that is representative for the group. We illustrate the benefits of the proposed algorithm on hierarchical clustering of motion capture sequences as well as on automatic music tagging.

Author Information

Emanuele Coviello (Amazon Music)
Antoni Chan (City University of Hong Kong)
Gert Lanckriet (U.C. San Diego)

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