diff --git a/fastlib/trunk/fastlib/optimization/lbfgs/lbfgs_impl.h b/fastlib/trunk/fastlib/optimization/lbfgs/lbfgs_impl.h
index 1acfc6dc8c..231a4b940e 100644
--- a/fastlib/trunk/fastlib/optimization/lbfgs/lbfgs_impl.h
+++ b/fastlib/trunk/fastlib/optimization/lbfgs/lbfgs_impl.h
@@ -620,7 +620,7 @@ std::string Lbfgs<OptimizedFunction>::ComputeProgress_() {
   double feasibility_error;
   optimized_function_->ComputeFeasibilityError(
       coordinates_, &feasibility_error);
-  double norm_grad=1.0/math::pow(2,la::Dot(gradient_.n_elements(), 
+  double norm_grad=1.0/std::pow(2,la::Dot(gradient_.n_elements(), 
       gradient_.ptr(), gradient_.ptr()));
   char buffer[1024];
   sprintf(buffer, "iteration:%i sigma:%lg lagrangian:%lg objective:%lg error:%lg "
diff --git a/fastlib/trunk/fastlib/optimization/lbfgs/optimization_utils.h b/fastlib/trunk/fastlib/optimization/lbfgs/optimization_utils.h
index 6e8e94facb..5d8cb1ddd7 100644
--- a/fastlib/trunk/fastlib/optimization/lbfgs/optimization_utils.h
+++ b/fastlib/trunk/fastlib/optimization/lbfgs/optimization_utils.h
@@ -170,9 +170,8 @@ class OptUtils {
     ones.SetAll(1.0);
     // This part of the sparsity constraint function formula can be
     // precomputed and it is the same for every iteration
-    double temp_pow_1_2_dimension = 1.0/std::pow(2,dimension)
-    double precomputed_sparse_factor
-      = -sparse_factor*(temp_pow_1_2_dimension-1)+temp_pow_1_2_dimension;
+    double temp_pow_1_2_dimension = 1.0/std::pow(2,dimension);
+    double precomputed_sparse_factor = -sparse_factor*(temp_pow_1_2_dimension-1)+temp_pow_1_2_dimension;
 
     for (index_t i=0; i<data->n_cols(); i++) {
       double *point=data->GetColumnPtr(i);