diff --git a/src/mlpack/methods/ann/layer/pooling_layer.hpp b/src/mlpack/methods/ann/layer/pooling_layer.hpp
index 9eb57aa2b6c..a33ffe9ac5d 100644
--- a/src/mlpack/methods/ann/layer/pooling_layer.hpp
+++ b/src/mlpack/methods/ann/layer/pooling_layer.hpp
@@ -10,6 +10,7 @@
 
 #include <mlpack/core.hpp>
 #include <mlpack/methods/ann/pooling_rules/mean_pooling.hpp>
+#include <mlpack/methods/ann/pooling_rules/max_pooling.hpp> 
 #include <mlpack/methods/ann/layer/layer_traits.hpp>
 
 namespace mlpack {
@@ -39,8 +40,9 @@ class PoolingLayer
    * @param kSize Size of the pooling window.
    * @param pooling The pooling strategy.
    */
-  PoolingLayer(const size_t kSize, PoolingRule pooling = PoolingRule()) :
-      kSize(kSize), pooling(pooling)
+  PoolingLayer(const size_t kSize,  const size_t stride = 1,
+              PoolingRule pooling = PoolingRule()) :
+      kSize(kSize), pooling(pooling), stride(stride)
   {
     // Nothing to do here.
   }
@@ -68,8 +70,8 @@ class PoolingLayer
   template<typename eT>
   void Forward(const arma::Cube<eT>& input, arma::Cube<eT>& output)
   {
-    output = arma::zeros<arma::Cube<eT> >(input.n_rows / kSize,
-                            input.n_cols / kSize, input.n_slices);
+    output = arma::zeros<arma::Cube<eT> >((input.n_rows - kSize) / stride + 1,
+                            (input.n_cols - kSize) / stride + 1, input.n_slices);
 
     for (size_t s = 0; s < input.n_slices; s++)
       Pooling(input.slice(s), output.slice(s));
@@ -155,6 +157,7 @@ class PoolingLayer
   {
     ar & data::CreateNVP(kSize, "kSize");
     ar & data::CreateNVP(pooling, "pooling");
+    ar & data::CreateNVP(stride, "stride");
   }
 
  private:
@@ -167,16 +170,16 @@ class PoolingLayer
   template<typename eT>
   void Pooling(const arma::Mat<eT>& input, arma::Mat<eT>& output)
   {
-
     const size_t rStep = kSize;
     const size_t cStep = kSize;
 
-    for (size_t j = 0; j < input.n_cols; j += cStep)
+    for (size_t j = 0, colidx = 0; j < output.n_cols; ++j, colidx += stride)
     {
-      for (size_t i = 0; i < input.n_rows; i += rStep)
+      for (size_t i = 0, rowidx = 0; i < output.n_rows; ++i, rowidx += stride)
       {
-        output(i / rStep, j / cStep) += pooling.Pooling(
-            input(arma::span(i, i + rStep - 1), arma::span(j, j + cStep - 1)));
+        output(i, j) += pooling.Pooling(
+            input(arma::span(rowidx, rowidx + rStep - 1), 
+              arma::span(colidx, colidx + cStep - 1)));
       }
     }
   }
@@ -215,6 +218,9 @@ class PoolingLayer
   //! Locally-stored size of the pooling window.
   size_t kSize;
 
+  //! Locally-stored stride value by which we move filter.
+  size_t stride;
+
   //! Locally-stored delta object.
   OutputDataType delta;
 
@@ -249,3 +255,4 @@ class LayerTraits<PoolingLayer<PoolingRule, InputDataType, OutputDataType> >
 } // namespace mlpack
 
 #endif
+