<p>Have you compiled mlpack without debugging symbols? If you're using the git master branch, then debugging and profiling symbols are enabled by default (you can disable with <code>-DDEBUG=OFF -DPROFILE=OFF</code>), and if you're using a release (2.0.1, for instance), then debugging and profiling symbols are disabled by default so that should not be an issue. And I assume you're compiling your program with <code>-O3</code> and without any debugging symbols or anything.</p>
<p>The EM algorithm may take some time to converge for a GMM. I think maybe to figure out what is going on here, you should try removing the HMM layer and just train a GMM on its own on the data. When you call <code>GMM::Train()</code>, you can pass in an instantiated <code>EMFit</code> object so that you can set the options, like the maximum number of iterations and the tolerance.</p>
<p>Based on your profile it seems like the major delay is possibly in these lines from <code>em_fit_impl.hpp</code> (lines 88--93):</p>
<pre><code>// Calculate the new value of the covariances using the updated
// conditional probabilities and the updated means.
arma::mat tmp = observations - (dists[i].Mean() *
arma::ones<arma::rowvec>(observations.n_cols));
arma::mat tmpB = tmp % (arma::ones<arma::vec>(observations.n_rows) *
trans(condProb.col(i)));
</code></pre>
<p>I wonder if that expression is not being optimized well?</p>
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