<p>In <a href="https://github.com/mlpack/mlpack/pull/749#discussion_r74688501">src/mlpack/methods/lsh_model/lshmodel.hpp</a>:</p>
<pre style='color:#555'>&gt; + * @article{Dong2008LSHModel,
&gt; + *  author = {Dong, Wei and Wang, Zhe and Josephson, William and Charikar,
&gt; + *      Moses and Li, Kai},
&gt; + *  title = {{Modeling LSH for performance tuning}},
&gt; + *  journal = {Proceeding of the 17th ACM conference on Information and
&gt; + *      knowledge mining - CIKM &#39;08},
&gt; + *  pages = {669},
&gt; + *  url = {http://portal.acm.org/citation.cfm?doid=1458082.1458172},
&gt; + *  year = {2008}
&gt; + * }
&gt; + * @endcode
&gt; + *
&gt; + * We use a different method to fit Gamma Distributions to pairwise distances.
&gt; + * Instead of the MLE method proposed in the paper above, we use the mlpack
&gt; + * class GammaDistribution, which implements fitting according to Thomas Minka&#39;s
&gt; + * work.
</pre>
<p>I think that Minka's method actually does return the MLE (as your convergence criterion tends to 0), so we are still estimating the MLE, just using a clever algorithm.  Correct me if I'm wrong about that.</p>

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