diff --git a/gtsam/linear/GaussianFactorGraph.cpp b/gtsam/linear/GaussianFactorGraph.cpp
index ad43b675b..4dd1af4e7 100644
--- a/gtsam/linear/GaussianFactorGraph.cpp
+++ b/gtsam/linear/GaussianFactorGraph.cpp
@@ -355,14 +355,6 @@ namespace gtsam {
      f->multiplyHessianAdd(alpha, x, y);
   }
 
-  ///* ************************************************************************* */
-  //void GaussianFactorGraph::multiplyHessianAdd(double alpha,
-  //    const double* x, double* y) const {
-  //vector<size_t> FactorKeys = getkeydim();
-  //BOOST_FOREACH(const GaussianFactor::shared_ptr& f, *this)
-  //    f->multiplyHessianAdd(alpha, x, y, FactorKeys);
-  //}
-
   /* ************************************************************************* */
   void GaussianFactorGraph::multiplyInPlace(const VectorValues& x, Errors& e) const {
     multiplyInPlace(x, e.begin());
@@ -392,42 +384,15 @@ namespace gtsam {
 
   /* ************************************************************************* */
   // x += alpha*A'*e
-void GaussianFactorGraph::transposeMultiplyAdd(double alpha, const Errors& e,
-    VectorValues& x) const {
-  // For each factor add the gradient contribution
-  Errors::const_iterator ei = e.begin();
-  BOOST_FOREACH(const sharedFactor& Ai_G, *this) {
-    JacobianFactor::shared_ptr Ai = convertToJacobianFactorPtr(Ai_G);
-    Ai->transposeMultiplyAdd(alpha, *(ei++), x);
+  void GaussianFactorGraph::transposeMultiplyAdd(double alpha, const Errors& e,
+      VectorValues& x) const {
+    // For each factor add the gradient contribution
+    Errors::const_iterator ei = e.begin();
+    BOOST_FOREACH(const sharedFactor& Ai_G, *this) {
+      JacobianFactor::shared_ptr Ai = convertToJacobianFactorPtr(Ai_G);
+      Ai->transposeMultiplyAdd(alpha, *(ei++), x);
+    }
   }
-}
-
-  ///* ************************************************************************* */
-  //void residual(const GaussianFactorGraph& fg, const VectorValues &x, VectorValues &r) {
-  //  Key i = 0 ;
-  //  BOOST_FOREACH(const GaussianFactor::shared_ptr& Ai_G, fg) {
-  //    JacobianFactor::shared_ptr Ai = convertToJacobianFactorPtr(Ai_G);
-  //    r[i] = Ai->getb();
-  //    i++;
-  //  }
-  //  VectorValues Ax = VectorValues::SameStructure(r);
-  //  multiply(fg,x,Ax);
-  //  axpy(-1.0,Ax,r);
-  //}
-
-  ///* ************************************************************************* */
-  //void multiply(const GaussianFactorGraph& fg, const VectorValues &x, VectorValues &r) {
-  //  r.setZero();
-  //  Key i = 0;
-  //  BOOST_FOREACH(const GaussianFactor::shared_ptr& Ai_G, fg) {
-  //    JacobianFactor::shared_ptr Ai = convertToJacobianFactorPtr(Ai_G);
-  //    Vector &y = r[i];
-  //    for(JacobianFactor::const_iterator j = Ai->begin(); j != Ai->end(); ++j) {
-  //      y += Ai->getA(j) * x[*j];
-  //    }
-  //    ++i;
-  //  }
-  //}
 
   /* ************************************************************************* */
   VectorValues GaussianFactorGraph::transposeMultiply(const Errors& e) const
diff --git a/gtsam/linear/GaussianFactorGraph.h b/gtsam/linear/GaussianFactorGraph.h
index 1861e2607..9b8a91a6e 100644
--- a/gtsam/linear/GaussianFactorGraph.h
+++ b/gtsam/linear/GaussianFactorGraph.h
@@ -310,10 +310,6 @@ namespace gtsam {
     void multiplyHessianAdd(double alpha, const VectorValues& x,
         VectorValues& y) const;
 
-    ///** y += alpha*A'A*x */
-    //void multiplyHessianAdd(double alpha, const double* x,
-    //    double* y) const;
-
     ///** In-place version e <- A*x that overwrites e. */
     void multiplyInPlace(const VectorValues& x, Errors& e) const;
 
diff --git a/gtsam/linear/tests/testGaussianFactorGraph.cpp b/gtsam/linear/tests/testGaussianFactorGraph.cpp
index 2fc1e359b..49a6e30e4 100644
--- a/gtsam/linear/tests/testGaussianFactorGraph.cpp
+++ b/gtsam/linear/tests/testGaussianFactorGraph.cpp
@@ -315,31 +315,6 @@ TEST( GaussianFactorGraph, multiplyHessianAdd2 )
   EXPECT(assert_equal(2*expected, actual));
 }
 
-/* ************************************************************************* */
-// Raw memory access
-//TEST( GaussianFactorGraph, multiplyHessianAdd3 )
-//{
-//  GaussianFactorGraph gfg = createGaussianFactorGraphWithHessianFactor();
-
-//  // brute force
-//  Matrix AtA; Vector eta; boost::tie(AtA,eta) = gfg.hessian();
-//  Vector X(6); X<<1,2,3,4,5,6;
-//  Vector Y(6); Y<<-450, -450, 300, 400, 2950, 3450;
-//  EXPECT(assert_equal(Y,AtA*X));
-
-//    double* x = &X[0];
-
-//    Vector fast_y = gtsam::zero(6);
-//    gfg.multiplyHessianAdd(1.0, x, fast_y.data());
-//    EXPECT(assert_equal(Y, fast_y));
-
-//    // now, do it with non-zero y
-//    gfg.multiplyHessianAdd(1.0, x, fast_y.data());
-//    EXPECT(assert_equal(2*Y, fast_y));
-
-//}
-
-
 /* ************************************************************************* */
 TEST( GaussianFactorGraph, matricesMixed )
 {
@@ -352,7 +327,6 @@ TEST( GaussianFactorGraph, matricesMixed )
   EXPECT(assert_equal(A.transpose()*b, eta));
 }
 
-
 /* ************************************************************************* */
 TEST( GaussianFactorGraph, gradientAtZero )
 {