<p>DropConnect Layer is based on Linear Layer, but with the difference that the weight matrix is multiplied by the random mask.I have also added tests, in which , the network architechture and size of hidden layer is same as that of the dropout layer in tests/feedforward_network_test.cpp.On my systems, the three tests are giving these classificationErrors: <br>
  Dropout         DropConnect<br>
1 0.0729288    0.0729288<br>
2 0.02              0.02<br>
3 0.134           0.068</p>

<hr>

<h4>You can view, comment on, or merge this pull request online at:</h4>
<p>&nbsp;&nbsp;<a href='https://github.com/mlpack/mlpack/pull/552'>https://github.com/mlpack/mlpack/pull/552</a></p>

<h4>Commit Summary</h4>
<ul>
  <li>Added drop_connect_layer.hpp. Fixes issue #413.</li>
  <li>Added tests for drop_connect_layer.hpp</li>
</ul>

<h4>File Changes</h4>
<ul>
  <li>
    <strong>A</strong>
    <a href="https://github.com/mlpack/mlpack/pull/552/files#diff-0">src/mlpack/methods/ann/layer/drop_connect_layer.hpp</a>
    (382)
  </li>
  <li>
    <strong>M</strong>
    <a href="https://github.com/mlpack/mlpack/pull/552/files#diff-1">src/mlpack/tests/feedforward_network_test.cpp</a>
    (128)
  </li>
</ul>

<h4>Patch Links:</h4>
<ul>
  <li><a href='https://github.com/mlpack/mlpack/pull/552.patch'>https://github.com/mlpack/mlpack/pull/552.patch</a></li>
  <li><a href='https://github.com/mlpack/mlpack/pull/552.diff'>https://github.com/mlpack/mlpack/pull/552.diff</a></li>
</ul>

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