<blockquote>
  <p>AdamOptimizer performs a learning rate decay internally (from a fixed given value) or not ?</p>
</blockquote>

<p>Yes, Adam does perform a learning rate decay.</p>

<p>You should have a look at how Adam works: </p>

<blockquote>
  <p>D. Kingma and J. Ba, “Adam: A method for stochastic optimization,”
  arXiv preprint arXiv:1412.6980, Dec. 2014. [Online]. Available:
  <a href="https://arxiv.org/abs/1412.6980" rel="nofollow noreferrer">https://arxiv.org/abs/1412.6980</a></p>
</blockquote>

<p>To sum it up: Adam is RMSProp with momentum and bias correction. A very nice explanation is here: <a href="http://sebastianruder.com/optimizing-gradient-descent/index.html#adam" rel="nofollow noreferrer">http://sebastianruder.com/optimizing-gradient-descent/index.html#adam</a></p>
Does make sense use dynamic learning rate in AdamOptimizer?
<p>I'm dvelopping a convolutional neural network for images recognition based on three own classes.
I built an AlexNet-based model to train.
I'd like to know two things:</p>

<ol>
<li><em>AdamOptimizer</em> performs a learning rate decay internally (from a fixed given value) or not ?</li>
<li>In case of not, can I use <code>tf.train.exponential_decay</code> to perform decay ?</li>
</ol>

<p>Small examples are apprecciated.
Thanks</p>