diff --git a/examples/vSLAMexample/vSFMexample.cpp b/examples/vSLAMexample/vSFMexample.cpp
index 6edd06465..8774b79f3 100644
--- a/examples/vSLAMexample/vSFMexample.cpp
+++ b/examples/vSLAMexample/vSFMexample.cpp
@@ -144,7 +144,7 @@ int main(int argc, char* argv[]) {
   // Optimize the graph
   cout << "*******************************************************" << endl;
   LevenbergMarquardtParams params;
-  params.lmVerbosity = LevenbergMarquardtParams::DAMPED;
+  params.verbosityLM = LevenbergMarquardtParams::DAMPED;
   visualSLAM::Values result = LevenbergMarquardtOptimizer(graph, initialEstimates, params).optimize();
 
   // Print final results
diff --git a/gtsam/nonlinear/DoglegOptimizer.cpp b/gtsam/nonlinear/DoglegOptimizer.cpp
index 374ef0c6b..84090d666 100644
--- a/gtsam/nonlinear/DoglegOptimizer.cpp
+++ b/gtsam/nonlinear/DoglegOptimizer.cpp
@@ -37,7 +37,7 @@ void DoglegOptimizer::iterate(void) {
   GaussianFactorGraph::Eliminate eliminationMethod = params_.getEliminationFunction();
 
   // Pull out parameters we'll use
-  const bool dlVerbose = (params_.dlVerbosity > DoglegParams::SILENT);
+  const bool dlVerbose = (params_.verbosityDL > DoglegParams::SILENT);
 
   // Do Dogleg iteration with either Multifrontal or Sequential elimination
   DoglegOptimizerImpl::IterationResult result;
diff --git a/gtsam/nonlinear/DoglegOptimizer.h b/gtsam/nonlinear/DoglegOptimizer.h
index 69d0503d7..7edb43ca9 100644
--- a/gtsam/nonlinear/DoglegOptimizer.h
+++ b/gtsam/nonlinear/DoglegOptimizer.h
@@ -32,16 +32,16 @@ class DoglegOptimizer;
 class DoglegParams : public SuccessiveLinearizationParams {
 public:
   /** See DoglegParams::dlVerbosity */
-  enum DLVerbosity {
+  enum VerbosityDL {
     SILENT,
     VERBOSE
   };
 
   double deltaInitial; ///< The initial trust region radius (default: 1.0)
-  DLVerbosity dlVerbosity; ///< The verbosity level for Dogleg (default: SILENT), see also NonlinearOptimizerParams::verbosity
+  VerbosityDL verbosityDL; ///< The verbosity level for Dogleg (default: SILENT), see also NonlinearOptimizerParams::verbosity
 
   DoglegParams() :
-    deltaInitial(1.0), dlVerbosity(SILENT) {}
+    deltaInitial(1.0), verbosityDL(SILENT) {}
 
   virtual ~DoglegParams() {}
 
diff --git a/gtsam/nonlinear/LevenbergMarquardtOptimizer.cpp b/gtsam/nonlinear/LevenbergMarquardtOptimizer.cpp
index 5295ce9ff..1b19cfe75 100644
--- a/gtsam/nonlinear/LevenbergMarquardtOptimizer.cpp
+++ b/gtsam/nonlinear/LevenbergMarquardtOptimizer.cpp
@@ -37,7 +37,7 @@ void LevenbergMarquardtOptimizer::iterate() {
 
   // Pull out parameters we'll use
   const NonlinearOptimizerParams::Verbosity nloVerbosity = params_.verbosity;
-  const LevenbergMarquardtParams::LMVerbosity lmVerbosity = params_.lmVerbosity;
+  const LevenbergMarquardtParams::VerbosityLM lmVerbosity = params_.verbosityLM;
 
   // Keep increasing lambda until we make make progress
   while(true) {
diff --git a/gtsam/nonlinear/LevenbergMarquardtOptimizer.h b/gtsam/nonlinear/LevenbergMarquardtOptimizer.h
index a03140166..c1fe55c26 100644
--- a/gtsam/nonlinear/LevenbergMarquardtOptimizer.h
+++ b/gtsam/nonlinear/LevenbergMarquardtOptimizer.h
@@ -32,7 +32,7 @@ class LevenbergMarquardtOptimizer;
 class LevenbergMarquardtParams : public SuccessiveLinearizationParams {
 public:
   /** See LevenbergMarquardtParams::lmVerbosity */
-  enum LMVerbosity {
+  enum VerbosityLM {
     SILENT,
     LAMBDA,
     TRYLAMBDA,
@@ -44,10 +44,10 @@ public:
   double lambdaInitial; ///< The initial Levenberg-Marquardt damping term (default: 1e-5)
   double lambdaFactor; ///< The amount by which to multiply or divide lambda when adjusting lambda (default: 10.0)
   double lambdaUpperBound; ///< The maximum lambda to try before assuming the optimization has failed (default: 1e5)
-  LMVerbosity lmVerbosity; ///< The verbosity level for Levenberg-Marquardt (default: SILENT), see also NonlinearOptimizerParams::verbosity
+  VerbosityLM verbosityLM; ///< The verbosity level for Levenberg-Marquardt (default: SILENT), see also NonlinearOptimizerParams::verbosity
 
   LevenbergMarquardtParams() :
-    lambdaInitial(1e-5), lambdaFactor(10.0), lambdaUpperBound(1e5), lmVerbosity(SILENT) {}
+    lambdaInitial(1e-5), lambdaFactor(10.0), lambdaUpperBound(1e5), verbosityLM(SILENT) {}
 
   virtual ~LevenbergMarquardtParams() {}