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<li class="navelem"><a class="el" href="namespacemlpack.html">mlpack</a></li><li class="navelem"><a class="el" href="namespacemlpack_1_1optimization.html">optimization</a></li><li class="navelem"><a class="el" href="classmlpack_1_1optimization_1_1AdaDelta.html">AdaDelta</a></li> </ul>
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<a href="#pub-methods">Public Member Functions</a> &#124;
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<div class="title">mlpack::optimization::AdaDelta&lt; DecomposableFunctionType &gt; Class Template Reference</div> </div>
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<p>Adadelta is an optimizer that uses two ideas to improve upon the two main drawbacks of the Adagrad method:
<a href="classmlpack_1_1optimization_1_1AdaDelta.html#details">More...</a></p>
<table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-methods"></a>
Public Member Functions</h2></td></tr>
<tr class="memitem:afe555f09f1ddd619ee0b48aeb5a8a321"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classmlpack_1_1optimization_1_1AdaDelta.html#afe555f09f1ddd619ee0b48aeb5a8a321">AdaDelta</a> (DecomposableFunctionType &amp;<a class="el" href="classmlpack_1_1optimization_1_1AdaDelta.html#ab2803c3e4c5d6d2e67797c570d5a57cd">function</a>, const double <a class="el" href="classmlpack_1_1optimization_1_1AdaDelta.html#abff6a9dd8b5252baa7d7fcda79fa8cee">rho</a>=0.95, const double <a class="el" href="classmlpack_1_1optimization_1_1AdaDelta.html#a8daa7c2a8b22f982cf1271c10334f046">eps</a>=1e-6, const size_t maxIterations=100000, const double tolerance=1e-5, const bool shuffle=true)</td></tr>
<tr class="memdesc:afe555f09f1ddd619ee0b48aeb5a8a321"><td class="mdescLeft">&#160;</td><td class="mdescRight">Construct the <a class="el" href="classmlpack_1_1optimization_1_1AdaDelta.html" title="Adadelta is an optimizer that uses two ideas to improve upon the two main drawbacks of the Adagrad me...">AdaDelta</a> optimizer with the given function and parameters. <a href="#afe555f09f1ddd619ee0b48aeb5a8a321">More...</a><br /></td></tr>
<tr class="separator:afe555f09f1ddd619ee0b48aeb5a8a321"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ab0e90a059982337e72c439c90c0ccd96"><td class="memItemLeft" align="right" valign="top">double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classmlpack_1_1optimization_1_1AdaDelta.html#ab0e90a059982337e72c439c90c0ccd96">Epsilon</a> () const </td></tr>
<tr class="memdesc:ab0e90a059982337e72c439c90c0ccd96"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the value used to initialise the mean squared gradient parameter. <a href="#ab0e90a059982337e72c439c90c0ccd96">More...</a><br /></td></tr>
<tr class="separator:ab0e90a059982337e72c439c90c0ccd96"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a9c73431710b7b132e04e58c7d41f0082"><td class="memItemLeft" align="right" valign="top">double &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classmlpack_1_1optimization_1_1AdaDelta.html#a9c73431710b7b132e04e58c7d41f0082">Epsilon</a> ()</td></tr>
<tr class="memdesc:a9c73431710b7b132e04e58c7d41f0082"><td class="mdescLeft">&#160;</td><td class="mdescRight">Modify the value used to initialise the mean squared gradient parameter. <a href="#a9c73431710b7b132e04e58c7d41f0082">More...</a><br /></td></tr>
<tr class="separator:a9c73431710b7b132e04e58c7d41f0082"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a0db4ce1195b7edbd8dea8e6746c6612f"><td class="memItemLeft" align="right" valign="top">const DecomposableFunctionType &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classmlpack_1_1optimization_1_1AdaDelta.html#a0db4ce1195b7edbd8dea8e6746c6612f">Function</a> () const </td></tr>
<tr class="memdesc:a0db4ce1195b7edbd8dea8e6746c6612f"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the instantiated function to be optimized. <a href="#a0db4ce1195b7edbd8dea8e6746c6612f">More...</a><br /></td></tr>
<tr class="separator:a0db4ce1195b7edbd8dea8e6746c6612f"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ad0205451386948b4b9c09a4d3fed59ad"><td class="memItemLeft" align="right" valign="top">DecomposableFunctionType &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classmlpack_1_1optimization_1_1AdaDelta.html#ad0205451386948b4b9c09a4d3fed59ad">Function</a> ()</td></tr>
<tr class="memdesc:ad0205451386948b4b9c09a4d3fed59ad"><td class="mdescLeft">&#160;</td><td class="mdescRight">Modify the instantiated function. <a href="#ad0205451386948b4b9c09a4d3fed59ad">More...</a><br /></td></tr>
<tr class="separator:ad0205451386948b4b9c09a4d3fed59ad"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a500124f0dc953ade5965c388106200c4"><td class="memItemLeft" align="right" valign="top">size_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classmlpack_1_1optimization_1_1AdaDelta.html#a500124f0dc953ade5965c388106200c4">MaxIterations</a> () const </td></tr>
<tr class="memdesc:a500124f0dc953ade5965c388106200c4"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the maximum number of iterations (0 indicates no limit). <a href="#a500124f0dc953ade5965c388106200c4">More...</a><br /></td></tr>
<tr class="separator:a500124f0dc953ade5965c388106200c4"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a99ee0230eedffd0dd9a20bc07024a4c8"><td class="memItemLeft" align="right" valign="top">size_t &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classmlpack_1_1optimization_1_1AdaDelta.html#a99ee0230eedffd0dd9a20bc07024a4c8">MaxIterations</a> ()</td></tr>
<tr class="memdesc:a99ee0230eedffd0dd9a20bc07024a4c8"><td class="mdescLeft">&#160;</td><td class="mdescRight">Modify the maximum number of iterations (0 indicates no limit). <a href="#a99ee0230eedffd0dd9a20bc07024a4c8">More...</a><br /></td></tr>
<tr class="separator:a99ee0230eedffd0dd9a20bc07024a4c8"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:af8697def83fd2451446dcfe97b7c4088"><td class="memItemLeft" align="right" valign="top">double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classmlpack_1_1optimization_1_1AdaDelta.html#af8697def83fd2451446dcfe97b7c4088">Optimize</a> (arma::mat &amp;iterate)</td></tr>
<tr class="memdesc:af8697def83fd2451446dcfe97b7c4088"><td class="mdescLeft">&#160;</td><td class="mdescRight">Optimize the given function using <a class="el" href="classmlpack_1_1optimization_1_1AdaDelta.html" title="Adadelta is an optimizer that uses two ideas to improve upon the two main drawbacks of the Adagrad me...">AdaDelta</a>. <a href="#af8697def83fd2451446dcfe97b7c4088">More...</a><br /></td></tr>
<tr class="separator:af8697def83fd2451446dcfe97b7c4088"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a613a359459c13f08be2f7e1fa9a82ccc"><td class="memItemLeft" align="right" valign="top">double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classmlpack_1_1optimization_1_1AdaDelta.html#a613a359459c13f08be2f7e1fa9a82ccc">Rho</a> () const </td></tr>
<tr class="memdesc:a613a359459c13f08be2f7e1fa9a82ccc"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the smoothing parameter. <a href="#a613a359459c13f08be2f7e1fa9a82ccc">More...</a><br /></td></tr>
<tr class="separator:a613a359459c13f08be2f7e1fa9a82ccc"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a2ab5deb5aa954f0b7300fffdec0d46b9"><td class="memItemLeft" align="right" valign="top">double &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classmlpack_1_1optimization_1_1AdaDelta.html#a2ab5deb5aa954f0b7300fffdec0d46b9">Rho</a> ()</td></tr>
<tr class="memdesc:a2ab5deb5aa954f0b7300fffdec0d46b9"><td class="mdescLeft">&#160;</td><td class="mdescRight">Modify the smoothing parameter. <a href="#a2ab5deb5aa954f0b7300fffdec0d46b9">More...</a><br /></td></tr>
<tr class="separator:a2ab5deb5aa954f0b7300fffdec0d46b9"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a05a6a896c254b958e12f33ca65d675f8"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classmlpack_1_1optimization_1_1AdaDelta.html#a05a6a896c254b958e12f33ca65d675f8">Shuffle</a> () const </td></tr>
<tr class="memdesc:a05a6a896c254b958e12f33ca65d675f8"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get whether or not the individual functions are shuffled. <a href="#a05a6a896c254b958e12f33ca65d675f8">More...</a><br /></td></tr>
<tr class="separator:a05a6a896c254b958e12f33ca65d675f8"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a8dc1f0b1a9f4e92065b3e807a04421b5"><td class="memItemLeft" align="right" valign="top">bool &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classmlpack_1_1optimization_1_1AdaDelta.html#a8dc1f0b1a9f4e92065b3e807a04421b5">Shuffle</a> ()</td></tr>
<tr class="memdesc:a8dc1f0b1a9f4e92065b3e807a04421b5"><td class="mdescLeft">&#160;</td><td class="mdescRight">Modify whether or not the individual functions are shuffled. <a href="#a8dc1f0b1a9f4e92065b3e807a04421b5">More...</a><br /></td></tr>
<tr class="separator:a8dc1f0b1a9f4e92065b3e807a04421b5"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:af982aa4fdc5b11f2d1f54a7aa3cf0b75"><td class="memItemLeft" align="right" valign="top">double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classmlpack_1_1optimization_1_1AdaDelta.html#af982aa4fdc5b11f2d1f54a7aa3cf0b75">Tolerance</a> () const </td></tr>
<tr class="memdesc:af982aa4fdc5b11f2d1f54a7aa3cf0b75"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the tolerance for termination. <a href="#af982aa4fdc5b11f2d1f54a7aa3cf0b75">More...</a><br /></td></tr>
<tr class="separator:af982aa4fdc5b11f2d1f54a7aa3cf0b75"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a5608018b50e044d47c02ae96b5e817a1"><td class="memItemLeft" align="right" valign="top">double &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classmlpack_1_1optimization_1_1AdaDelta.html#a5608018b50e044d47c02ae96b5e817a1">Tolerance</a> ()</td></tr>
<tr class="memdesc:a5608018b50e044d47c02ae96b5e817a1"><td class="mdescLeft">&#160;</td><td class="mdescRight">Modify the tolerance for termination. <a href="#a5608018b50e044d47c02ae96b5e817a1">More...</a><br /></td></tr>
<tr class="separator:a5608018b50e044d47c02ae96b5e817a1"><td class="memSeparator" colspan="2">&#160;</td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pri-attribs"></a>
Private Attributes</h2></td></tr>
<tr class="memitem:a8daa7c2a8b22f982cf1271c10334f046"><td class="memItemLeft" align="right" valign="top">double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classmlpack_1_1optimization_1_1AdaDelta.html#a8daa7c2a8b22f982cf1271c10334f046">eps</a></td></tr>
<tr class="memdesc:a8daa7c2a8b22f982cf1271c10334f046"><td class="mdescLeft">&#160;</td><td class="mdescRight">The value used to initialise the mean squared gradient parameter. <a href="#a8daa7c2a8b22f982cf1271c10334f046">More...</a><br /></td></tr>
<tr class="separator:a8daa7c2a8b22f982cf1271c10334f046"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ab2803c3e4c5d6d2e67797c570d5a57cd"><td class="memItemLeft" align="right" valign="top">DecomposableFunctionType &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classmlpack_1_1optimization_1_1AdaDelta.html#ab2803c3e4c5d6d2e67797c570d5a57cd">function</a></td></tr>
<tr class="memdesc:ab2803c3e4c5d6d2e67797c570d5a57cd"><td class="mdescLeft">&#160;</td><td class="mdescRight">The instantiated function. <a href="#ab2803c3e4c5d6d2e67797c570d5a57cd">More...</a><br /></td></tr>
<tr class="separator:ab2803c3e4c5d6d2e67797c570d5a57cd"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a57d20d8ef11d20b0b064dfc0651f62c4"><td class="memItemLeft" align="right" valign="top">size_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classmlpack_1_1optimization_1_1AdaDelta.html#a57d20d8ef11d20b0b064dfc0651f62c4">maxIterations</a></td></tr>
<tr class="memdesc:a57d20d8ef11d20b0b064dfc0651f62c4"><td class="mdescLeft">&#160;</td><td class="mdescRight">The maximum number of allowed iterations. <a href="#a57d20d8ef11d20b0b064dfc0651f62c4">More...</a><br /></td></tr>
<tr class="separator:a57d20d8ef11d20b0b064dfc0651f62c4"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:abff6a9dd8b5252baa7d7fcda79fa8cee"><td class="memItemLeft" align="right" valign="top">double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classmlpack_1_1optimization_1_1AdaDelta.html#abff6a9dd8b5252baa7d7fcda79fa8cee">rho</a></td></tr>
<tr class="memdesc:abff6a9dd8b5252baa7d7fcda79fa8cee"><td class="mdescLeft">&#160;</td><td class="mdescRight">The smoothing parameter. <a href="#abff6a9dd8b5252baa7d7fcda79fa8cee">More...</a><br /></td></tr>
<tr class="separator:abff6a9dd8b5252baa7d7fcda79fa8cee"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a3056efd630103c20bf94cd775974ca1b"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classmlpack_1_1optimization_1_1AdaDelta.html#a3056efd630103c20bf94cd775974ca1b">shuffle</a></td></tr>
<tr class="memdesc:a3056efd630103c20bf94cd775974ca1b"><td class="mdescLeft">&#160;</td><td class="mdescRight">Controls whether or not the individual functions are shuffled when iterating. <a href="#a3056efd630103c20bf94cd775974ca1b">More...</a><br /></td></tr>
<tr class="separator:a3056efd630103c20bf94cd775974ca1b"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a8cf0f7421523cd4592fc881f3f80d112"><td class="memItemLeft" align="right" valign="top">double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classmlpack_1_1optimization_1_1AdaDelta.html#a8cf0f7421523cd4592fc881f3f80d112">tolerance</a></td></tr>
<tr class="memdesc:a8cf0f7421523cd4592fc881f3f80d112"><td class="mdescLeft">&#160;</td><td class="mdescRight">The tolerance for termination. <a href="#a8cf0f7421523cd4592fc881f3f80d112">More...</a><br /></td></tr>
<tr class="separator:a8cf0f7421523cd4592fc881f3f80d112"><td class="memSeparator" colspan="2">&#160;</td></tr>
</table>
<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
<div class="textblock"><h3>template&lt;typename DecomposableFunctionType&gt;<br />
class mlpack::optimization::AdaDelta&lt; DecomposableFunctionType &gt;</h3>
<p>Adadelta is an optimizer that uses two ideas to improve upon the two main drawbacks of the Adagrad method: </p>
<ul>
<li>Accumulate Over Window</li>
<li>Correct Units with Hessian Approximation</li>
</ul>
<p>For more information, see the following.</p>
<div class="fragment"><div class="line">@article{Zeiler2012,</div><div class="line"> author = {Matthew D. Zeiler},</div><div class="line"> title = {{ADADELTA:} An Adaptive Learning Rate Method},</div><div class="line"> journal = {CoRR},</div><div class="line"> year = {2012}</div><div class="line">}</div></div><!-- fragment --><p>For <a class="el" href="classmlpack_1_1optimization_1_1AdaDelta.html" title="Adadelta is an optimizer that uses two ideas to improve upon the two main drawbacks of the Adagrad me...">AdaDelta</a> to work, a DecomposableFunctionType template parameter is required. This class must implement the following function:</p>
<p>size_t NumFunctions(); double Evaluate(const arma::mat&amp; coordinates, const size_t i); void Gradient(const arma::mat&amp; coordinates, const size_t i, arma::mat&amp; gradient);</p>
<p>NumFunctions() should return the number of functions ( <img class="formulaInl" alt="$n$" src="form_33.png"/>), and in the other two functions, the parameter i refers to which individual function (or gradient) is being evaluated. So, for the case of a data-dependent function, such as NCA (see <a class="el" href="classmlpack_1_1nca_1_1NCA.html" title="An implementation of Neighborhood Components Analysis, both a linear dimensionality reduction techniq...">mlpack::nca::NCA</a>), NumFunctions() should return the number of points in the dataset, and Evaluate(coordinates, 0) will evaluate the objective function on the first point in the dataset (presumably, the dataset is held internally in the DecomposableFunctionType).</p>
<dl class="tparams"><dt>Template Parameters</dt><dd>
<table class="tparams">
<tr><td class="paramname">DecomposableFunctionType</td><td>Decomposable objective function type to be minimized. </td></tr>
</table>
</dd>
</dl>
<p>Definition at line <a class="el" href="ada__delta_8hpp_source.html#l00063">63</a> of file <a class="el" href="ada__delta_8hpp_source.html">ada_delta.hpp</a>.</p>
</div><h2 class="groupheader">Constructor &amp; Destructor Documentation</h2>
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<td class="memname"><a class="el" href="classmlpack_1_1optimization_1_1AdaDelta.html">mlpack::optimization::AdaDelta</a>&lt; DecomposableFunctionType &gt;::<a class="el" href="classmlpack_1_1optimization_1_1AdaDelta.html">AdaDelta</a> </td>
<td>(</td>
<td class="paramtype">DecomposableFunctionType &amp;&#160;</td>
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<td class="paramname"><em>rho</em> = <code>0.95</code>, </td>
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<p>Construct the <a class="el" href="classmlpack_1_1optimization_1_1AdaDelta.html" title="Adadelta is an optimizer that uses two ideas to improve upon the two main drawbacks of the Adagrad me...">AdaDelta</a> optimizer with the given function and parameters. </p>
<p>The defaults here are not necessarily good for the given problem, so it is suggested that the values used be tailored to the task at hand. The maximum number of iterations refers to the maximum number of points that are processed (i.e., one iteration equals one point; one iteration does not equal one pass over the dataset).</p>
<dl class="params"><dt>Parameters</dt><dd>
<table class="params">
<tr><td class="paramname">function</td><td>Function to be optimized (minimized). </td></tr>
<tr><td class="paramname">rho</td><td>Smoothing constant </td></tr>
<tr><td class="paramname">eps</td><td>Value used to initialise the mean squared gradient parameter. </td></tr>
<tr><td class="paramname">maxIterations</td><td>Maximum number of iterations allowed (0 means no limit). </td></tr>
<tr><td class="paramname">tolerance</td><td>Maximum absolute tolerance to terminate algorithm. </td></tr>
<tr><td class="paramname">shuffle</td><td>If true, the function order is shuffled; otherwise, each function is visited in linear order. </td></tr>
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<h2 class="groupheader">Member Function Documentation</h2>
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<p>Get the value used to initialise the mean squared gradient parameter. </p>
<p>Definition at line <a class="el" href="ada__delta_8hpp_source.html#l00111">111</a> of file <a class="el" href="ada__delta_8hpp_source.html">ada_delta.hpp</a>.</p>
<p>References <a class="el" href="ada__delta_8hpp_source.html#l00138">mlpack::optimization::AdaDelta&lt; DecomposableFunctionType &gt;::eps</a>.</p>
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<p>Modify the value used to initialise the mean squared gradient parameter. </p>
<p>Definition at line <a class="el" href="ada__delta_8hpp_source.html#l00113">113</a> of file <a class="el" href="ada__delta_8hpp_source.html">ada_delta.hpp</a>.</p>
<p>References <a class="el" href="ada__delta_8hpp_source.html#l00138">mlpack::optimization::AdaDelta&lt; DecomposableFunctionType &gt;::eps</a>.</p>
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<p>Get the instantiated function to be optimized. </p>
<p>Definition at line <a class="el" href="ada__delta_8hpp_source.html#l00101">101</a> of file <a class="el" href="ada__delta_8hpp_source.html">ada_delta.hpp</a>.</p>
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<p>Modify the instantiated function. </p>
<p>Definition at line <a class="el" href="ada__delta_8hpp_source.html#l00103">103</a> of file <a class="el" href="ada__delta_8hpp_source.html">ada_delta.hpp</a>.</p>
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<p>Get the maximum number of iterations (0 indicates no limit). </p>
<p>Definition at line <a class="el" href="ada__delta_8hpp_source.html#l00116">116</a> of file <a class="el" href="ada__delta_8hpp_source.html">ada_delta.hpp</a>.</p>
<p>References <a class="el" href="ada__delta_8hpp_source.html#l00141">mlpack::optimization::AdaDelta&lt; DecomposableFunctionType &gt;::maxIterations</a>.</p>
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<p>Modify the maximum number of iterations (0 indicates no limit). </p>
<p>Definition at line <a class="el" href="ada__delta_8hpp_source.html#l00118">118</a> of file <a class="el" href="ada__delta_8hpp_source.html">ada_delta.hpp</a>.</p>
<p>References <a class="el" href="ada__delta_8hpp_source.html#l00141">mlpack::optimization::AdaDelta&lt; DecomposableFunctionType &gt;::maxIterations</a>.</p>
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<td class="memname">double <a class="el" href="classmlpack_1_1optimization_1_1AdaDelta.html">mlpack::optimization::AdaDelta</a>&lt; DecomposableFunctionType &gt;::Optimize </td>
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<p>Optimize the given function using <a class="el" href="classmlpack_1_1optimization_1_1AdaDelta.html" title="Adadelta is an optimizer that uses two ideas to improve upon the two main drawbacks of the Adagrad me...">AdaDelta</a>. </p>
<p>The given starting point will be modified to store the finishing point of the algorithm, and the final objective value is returned.</p>
<dl class="params"><dt>Parameters</dt><dd>
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<tr><td class="paramname">iterate</td><td>Starting point (will be modified). </td></tr>
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<dl class="section return"><dt>Returns</dt><dd>Objective value of the final point. </dd></dl>
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<p>Get the smoothing parameter. </p>
<p>Definition at line <a class="el" href="ada__delta_8hpp_source.html#l00106">106</a> of file <a class="el" href="ada__delta_8hpp_source.html">ada_delta.hpp</a>.</p>
<p>References <a class="el" href="ada__delta_8hpp_source.html#l00135">mlpack::optimization::AdaDelta&lt; DecomposableFunctionType &gt;::rho</a>.</p>
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<p>Modify the smoothing parameter. </p>
<p>Definition at line <a class="el" href="ada__delta_8hpp_source.html#l00108">108</a> of file <a class="el" href="ada__delta_8hpp_source.html">ada_delta.hpp</a>.</p>
<p>References <a class="el" href="ada__delta_8hpp_source.html#l00135">mlpack::optimization::AdaDelta&lt; DecomposableFunctionType &gt;::rho</a>.</p>
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<p>Get whether or not the individual functions are shuffled. </p>
<p>Definition at line <a class="el" href="ada__delta_8hpp_source.html#l00126">126</a> of file <a class="el" href="ada__delta_8hpp_source.html">ada_delta.hpp</a>.</p>
<p>References <a class="el" href="ada__delta_8hpp_source.html#l00148">mlpack::optimization::AdaDelta&lt; DecomposableFunctionType &gt;::shuffle</a>.</p>
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<p>Modify whether or not the individual functions are shuffled. </p>
<p>Definition at line <a class="el" href="ada__delta_8hpp_source.html#l00128">128</a> of file <a class="el" href="ada__delta_8hpp_source.html">ada_delta.hpp</a>.</p>
<p>References <a class="el" href="ada__delta_8hpp_source.html#l00148">mlpack::optimization::AdaDelta&lt; DecomposableFunctionType &gt;::shuffle</a>.</p>
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<p>Get the tolerance for termination. </p>
<p>Definition at line <a class="el" href="ada__delta_8hpp_source.html#l00121">121</a> of file <a class="el" href="ada__delta_8hpp_source.html">ada_delta.hpp</a>.</p>
<p>References <a class="el" href="ada__delta_8hpp_source.html#l00144">mlpack::optimization::AdaDelta&lt; DecomposableFunctionType &gt;::tolerance</a>.</p>
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<p>Modify the tolerance for termination. </p>
<p>Definition at line <a class="el" href="ada__delta_8hpp_source.html#l00123">123</a> of file <a class="el" href="ada__delta_8hpp_source.html">ada_delta.hpp</a>.</p>
<p>References <a class="el" href="ada__delta_8hpp_source.html#l00144">mlpack::optimization::AdaDelta&lt; DecomposableFunctionType &gt;::tolerance</a>.</p>
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<h2 class="groupheader">Member Data Documentation</h2>
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<p>The value used to initialise the mean squared gradient parameter. </p>
<p>Definition at line <a class="el" href="ada__delta_8hpp_source.html#l00138">138</a> of file <a class="el" href="ada__delta_8hpp_source.html">ada_delta.hpp</a>.</p>
<p>Referenced by <a class="el" href="ada__delta_8hpp_source.html#l00111">mlpack::optimization::AdaDelta&lt; DecomposableFunctionType &gt;::Epsilon()</a>.</p>
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<p>The instantiated function. </p>
<p>Definition at line <a class="el" href="ada__delta_8hpp_source.html#l00132">132</a> of file <a class="el" href="ada__delta_8hpp_source.html">ada_delta.hpp</a>.</p>
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<p>The maximum number of allowed iterations. </p>
<p>Definition at line <a class="el" href="ada__delta_8hpp_source.html#l00141">141</a> of file <a class="el" href="ada__delta_8hpp_source.html">ada_delta.hpp</a>.</p>
<p>Referenced by <a class="el" href="ada__delta_8hpp_source.html#l00116">mlpack::optimization::AdaDelta&lt; DecomposableFunctionType &gt;::MaxIterations()</a>.</p>
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<p>The smoothing parameter. </p>
<p>Definition at line <a class="el" href="ada__delta_8hpp_source.html#l00135">135</a> of file <a class="el" href="ada__delta_8hpp_source.html">ada_delta.hpp</a>.</p>
<p>Referenced by <a class="el" href="ada__delta_8hpp_source.html#l00106">mlpack::optimization::AdaDelta&lt; DecomposableFunctionType &gt;::Rho()</a>.</p>
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<td class="memname">bool <a class="el" href="classmlpack_1_1optimization_1_1AdaDelta.html">mlpack::optimization::AdaDelta</a>&lt; DecomposableFunctionType &gt;::shuffle</td>
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<p>Controls whether or not the individual functions are shuffled when iterating. </p>
<p>Definition at line <a class="el" href="ada__delta_8hpp_source.html#l00148">148</a> of file <a class="el" href="ada__delta_8hpp_source.html">ada_delta.hpp</a>.</p>
<p>Referenced by <a class="el" href="ada__delta_8hpp_source.html#l00126">mlpack::optimization::AdaDelta&lt; DecomposableFunctionType &gt;::Shuffle()</a>.</p>
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<td class="memname">double <a class="el" href="classmlpack_1_1optimization_1_1AdaDelta.html">mlpack::optimization::AdaDelta</a>&lt; DecomposableFunctionType &gt;::tolerance</td>
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<p>The tolerance for termination. </p>
<p>Definition at line <a class="el" href="ada__delta_8hpp_source.html#l00144">144</a> of file <a class="el" href="ada__delta_8hpp_source.html">ada_delta.hpp</a>.</p>
<p>Referenced by <a class="el" href="ada__delta_8hpp_source.html#l00121">mlpack::optimization::AdaDelta&lt; DecomposableFunctionType &gt;::Tolerance()</a>.</p>
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<hr/>The documentation for this class was generated from the following file:<ul>
<li>src/mlpack/core/optimizers/adadelta/<a class="el" href="ada__delta_8hpp_source.html">ada_delta.hpp</a></li>
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