(exp(lp), size(t1)), [0.1:0.1:0.9]);
</pre>

<p>We train the hyperparameters using <a href="../util/minimize.m">minimize</a>,
 to minimize the negative log
 marginal likelihood. We allow for <tt>40</tt> function evaluations,
 and specify that inference should be done with the Expectation
 Propagation (EP) inference method <a href="../inf/infEP.m">@infEP</a>,
 and pass the usual parameters. Training is done using algorithm 3.5
 and 5.2 from the <a href="http://gaussianprocess.org/gpml/">gpml
 book</a>.  When