diff --git a/src/mlpack/core/optimizers/CMakeLists.txt b/src/mlpack/core/optimizers/CMakeLists.txt
index 3e16f0267e..c5163da22c 100644
--- a/src/mlpack/core/optimizers/CMakeLists.txt
+++ b/src/mlpack/core/optimizers/CMakeLists.txt
@@ -1,4 +1,6 @@
 set(DIRS
+  adadelta
+  adam
   aug_lagrangian
   lbfgs
   minibatch_sgd
diff --git a/src/mlpack/core/optimizers/adadelta/ada_delta.hpp b/src/mlpack/core/optimizers/adadelta/ada_delta.hpp
index dbe58868dd..067a4bfbf0 100644
--- a/src/mlpack/core/optimizers/adadelta/ada_delta.hpp
+++ b/src/mlpack/core/optimizers/adadelta/ada_delta.hpp
@@ -1,3 +1,12 @@
+/**
+ * @file ada_delta.hpp
+ * @author Ryan Curtin
+ * @author Vasanth Kalingeri
+ *
+ * Implementation of the Adadelta optimizer. Adadelta is an optimizer that
+ * dynamically adapts over time using only first order information.
+ * Additionally, Adadelta requires no manual tuning of a learning rate.
+ */
 #ifndef __MLPACK_CORE_OPTIMIZERS_ADADELTA_ADA_DELTA_HPP
 #define __MLPACK_CORE_OPTIMIZERS_ADADELTA_ADA_DELTA_HPP
 
@@ -50,9 +59,9 @@ class AdaDelta
 {
  public:
   /**
-   * Construct the AdaDelta optimizer with the given function and parameters. 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
+   * Construct the AdaDelta optimizer with the given function and parameters.
+   * 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).
@@ -74,8 +83,8 @@ class AdaDelta
       const bool shuffle = true);
   
   /**
-   * Optimize the given function using AdaDelta. The given starting point will be
-   * modified to store the finishing point of the algorithm, and the final
+   * Optimize the given function using AdaDelta. The given starting point will
+   * be modified to store the finishing point of the algorithm, and the final
    * objective value is returned.
    *
    * @param iterate Starting point (will be modified).
diff --git a/src/mlpack/core/optimizers/adadelta/ada_delta_impl.hpp b/src/mlpack/core/optimizers/adadelta/ada_delta_impl.hpp
index ac08a62047..41b3d027d0 100644
--- a/src/mlpack/core/optimizers/adadelta/ada_delta_impl.hpp
+++ b/src/mlpack/core/optimizers/adadelta/ada_delta_impl.hpp
@@ -1,3 +1,10 @@
+/**
+ * @file ada_delta_impl.hpp
+ * @author Ryan Curtin
+ * @author Vasanth Kalingeri
+ *
+ * Implementation of the Adadelta optimizer.
+ */
 #ifndef __MLPACK_CORE_OPTIMIZERS_ADADELTA_ADA_DELTA_IMPL_HPP
 #define __MLPACK_CORE_OPTIMIZERS_ADADELTA_ADA_DELTA_IMPL_HPP
 
@@ -73,8 +80,8 @@ double AdaDelta<DecomposableFunctionType>::Optimize(arma::mat& iterate)
 
       if (std::abs(lastObjective - overallObjective) < tolerance)
       {
-        Log::Info << "AdaDelta: minimized within tolerance " << tolerance << "; "
-            << "terminating optimization." << std::endl;
+        Log::Info << "AdaDelta: minimized within tolerance " << tolerance
+            << "; terminating optimization." << std::endl;
         return overallObjective;
       }
 
@@ -114,8 +121,8 @@ double AdaDelta<DecomposableFunctionType>::Optimize(arma::mat& iterate)
       overallObjective += function.Evaluate(iterate, currentFunction);
   }
 
-  Log::Info << "AdaDelta: maximum iterations (" << maxIterations << ") reached; "
-      << "terminating optimization." << std::endl;
+  Log::Info << "AdaDelta: maximum iterations (" << maxIterations
+      << ") reached; terminating optimization." << std::endl;
   // Calculate final objective.
   overallObjective = 0;
   for (size_t i = 0; i < numFunctions; ++i)