diff --git a/cpp/testIterative.cpp b/cpp/testIterative.cpp
index 86fcf4bc4..0a1b4ad50 100644
--- a/cpp/testIterative.cpp
+++ b/cpp/testIterative.cpp
@@ -18,58 +18,58 @@ using namespace boost::assign;
 using namespace std;
 using namespace gtsam;
 
-///* ************************************************************************* */
-//TEST( Iterative, steepestDescent )
-//{
-//	// Expected solution
-//	Ordering ord;
-//	ord += "l1", "x1", "x2";
-//	GaussianFactorGraph fg = createGaussianFactorGraph();
-//	VectorConfig expected = fg.optimize(ord); // destructive
-//
-//	// Do gradient descent
-//	GaussianFactorGraph fg2 = createGaussianFactorGraph();
-//	VectorConfig zero = createZeroDelta();
-//	bool verbose = false;
-//	VectorConfig actual = steepestDescent(fg2, zero, verbose);
-//	CHECK(assert_equal(expected,actual,1e-2));
-//}
-//
-///* ************************************************************************* */
-//TEST( Iterative, conjugateGradientDescent )
-//{
-//	// Expected solution
-//	Ordering ord;
-//	ord += "l1", "x1", "x2";
-//	GaussianFactorGraph fg = createGaussianFactorGraph();
-//	VectorConfig expected = fg.optimize(ord); // destructive
-//
-//	// create graph and get matrices
-//	GaussianFactorGraph fg2 = createGaussianFactorGraph();
-//	Matrix A;
-//	Vector b;
-//	Vector x0 = gtsam::zero(6);
-//	boost::tie(A, b) = fg2.matrix(ord);
-//	Vector expectedX = Vector_(6, -0.1, 0.1, -0.1, -0.1, 0.1, -0.2);
-//
-//	// Do conjugate gradient descent, System version
-//	System Ab(A, b);
-//	Vector actualX = conjugateGradientDescent(Ab, x0);
-//	CHECK(assert_equal(expectedX,actualX,1e-9));
-//
-//	// Do conjugate gradient descent, Matrix version
-//	Vector actualX2 = conjugateGradientDescent(A, b, x0);
-//	CHECK(assert_equal(expectedX,actualX2,1e-9));
-//
-//	// Do conjugate gradient descent on factor graph
-//	VectorConfig zero = createZeroDelta();
-//	VectorConfig actual = conjugateGradientDescent(fg2, zero);
-//	CHECK(assert_equal(expected,actual,1e-2));
-//
-//	// Test method
-//	VectorConfig actual2 = fg2.conjugateGradientDescent(zero);
-//	CHECK(assert_equal(expected,actual2,1e-2));
-//}
+/* ************************************************************************* */
+TEST( Iterative, steepestDescent )
+{
+	// Expected solution
+	Ordering ord;
+	ord += "l1", "x1", "x2";
+	GaussianFactorGraph fg = createGaussianFactorGraph();
+	VectorConfig expected = fg.optimize(ord); // destructive
+
+	// Do gradient descent
+	GaussianFactorGraph fg2 = createGaussianFactorGraph();
+	VectorConfig zero = createZeroDelta();
+	bool verbose = false;
+	VectorConfig actual = steepestDescent(fg2, zero, verbose);
+	CHECK(assert_equal(expected,actual,1e-2));
+}
+
+/* ************************************************************************* */
+TEST( Iterative, conjugateGradientDescent )
+{
+	// Expected solution
+	Ordering ord;
+	ord += "l1", "x1", "x2";
+	GaussianFactorGraph fg = createGaussianFactorGraph();
+	VectorConfig expected = fg.optimize(ord); // destructive
+
+	// create graph and get matrices
+	GaussianFactorGraph fg2 = createGaussianFactorGraph();
+	Matrix A;
+	Vector b;
+	Vector x0 = gtsam::zero(6);
+	boost::tie(A, b) = fg2.matrix(ord);
+	Vector expectedX = Vector_(6, -0.1, 0.1, -0.1, -0.1, 0.1, -0.2);
+
+	// Do conjugate gradient descent, System version
+	System Ab(A, b);
+	Vector actualX = conjugateGradientDescent(Ab, x0);
+	CHECK(assert_equal(expectedX,actualX,1e-9));
+
+	// Do conjugate gradient descent, Matrix version
+	Vector actualX2 = conjugateGradientDescent(A, b, x0);
+	CHECK(assert_equal(expectedX,actualX2,1e-9));
+
+	// Do conjugate gradient descent on factor graph
+	VectorConfig zero = createZeroDelta();
+	VectorConfig actual = conjugateGradientDescent(fg2, zero);
+	CHECK(assert_equal(expected,actual,1e-2));
+
+	// Test method
+	VectorConfig actual2 = fg2.conjugateGradientDescent(zero);
+	CHECK(assert_equal(expected,actual2,1e-2));
+}
 
 /* ************************************************************************* *
 TEST( Iterative, conjugateGradientDescent_hard_constraint )