diff --git a/examples/sampled_function/CMakeLists.txt b/examples/sampled_function/CMakeLists.txt
index 57f31d1..8a17cad 100644
--- a/examples/sampled_function/CMakeLists.txt
+++ b/examples/sampled_function/CMakeLists.txt
@@ -29,4 +29,4 @@
 # Author: vitus@google.com (Michael Vitus)
 
 add_executable(sampled_function sampled_function.cc)
-target_link_libraries(sampled_function ceres)
+target_link_libraries(sampled_function Ceres::ceres)
diff --git a/examples/sampled_function/README.md b/examples/sampled_function/README.md
index 77ce365..ef1af43 100644
--- a/examples/sampled_function/README.md
+++ b/examples/sampled_function/README.md
@@ -15,7 +15,7 @@
 interpolation method requires knowledge of the function derivatives at the
 control points, however we only know the function values. Consequently, we will
 use the data to estimate derivatives at the control points. The choice of how to
-compute the derivatives is not unique and Ceres uses the Catmull–Rom Spline
+compute the derivatives is not unique and Ceres uses the Catmull-Rom Spline
 variant which uses `0.5 * (p_{k+1} - p_{k-1})` as the derivative for control
 point `p_k.` This produces a first order differentiable interpolating
 function. The two dimensional interpolation scheme is a generalization of the
diff --git a/examples/sampled_function/sampled_function.cc b/examples/sampled_function/sampled_function.cc
index 093276a..e96018d 100644
--- a/examples/sampled_function/sampled_function.cc
+++ b/examples/sampled_function/sampled_function.cc
@@ -35,35 +35,35 @@
 #include "ceres/cubic_interpolation.h"
 #include "glog/logging.h"
 
-using ceres::Grid1D;
-using ceres::CubicInterpolator;
 using ceres::AutoDiffCostFunction;
 using ceres::CostFunction;
+using ceres::CubicInterpolator;
+using ceres::Grid1D;
 using ceres::Problem;
-using ceres::Solver;
 using ceres::Solve;
+using ceres::Solver;
 
 // A simple cost functor that interfaces an interpolated table of
 // values with automatic differentiation.
 struct InterpolatedCostFunctor {
   explicit InterpolatedCostFunctor(
-      const CubicInterpolator<Grid1D<double> >& interpolator)
-      : interpolator_(interpolator) {
-  }
+      const CubicInterpolator<Grid1D<double>>& interpolator)
+      : interpolator_(interpolator) {}
 
-  template<typename T> bool operator()(const T* x, T* residuals) const {
+  template <typename T>
+  bool operator()(const T* x, T* residuals) const {
     interpolator_.Evaluate(*x, residuals);
     return true;
   }
 
   static CostFunction* Create(
-      const CubicInterpolator<Grid1D<double> >& interpolator) {
+      const CubicInterpolator<Grid1D<double>>& interpolator) {
     return new AutoDiffCostFunction<InterpolatedCostFunctor, 1, 1>(
         new InterpolatedCostFunctor(interpolator));
   }
 
  private:
-  const CubicInterpolator<Grid1D<double> >& interpolator_;
+  const CubicInterpolator<Grid1D<double>>& interpolator_;
 };
 
 int main(int argc, char** argv) {
@@ -77,7 +77,7 @@
   }
 
   Grid1D<double> array(values, 0, kNumSamples);
-  CubicInterpolator<Grid1D<double> > interpolator(array);
+  CubicInterpolator<Grid1D<double>> interpolator(array);
 
   double x = 1.0;
   Problem problem;