title: L2 regularization for the fully connected parameters in CNN
body: <p>In <a href="https://github.com/tensorflow/tensorflow/blob/master/tensorflow/models/image/mnist/convolutional.py#L236" rel="nofollow">this</a> example for tensorflow, it used L2 regularization for the fully connected parameters.:</p>
  
  <pre><code>regularizers = (tf.nn.l2_loss(fc1_weights) + tf.nn.l2_loss(fc1_biases) +
                    tf.nn.l2_loss(fc2_weights) + tf.nn.l2_loss(fc2_biases))
  </code></pre>
  
  <p>what is it? why fully connected parameters used here? and how it improve the prformance?</p>