diff --git a/gtsam.h b/gtsam.h
index b80ddd26e..a78c6901b 100644
--- a/gtsam.h
+++ b/gtsam.h
@@ -1011,7 +1011,6 @@ class Marginals {
 #include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
 class LevenbergMarquardtParams {
   LevenbergMarquardtParams();
-  LevenbergMarquardtParams(double initial, double factor, double bound, size_t verbose);
   void print(string s) const;
 
   double getMaxIterations() const;
diff --git a/gtsam/nonlinear/LevenbergMarquardtOptimizer.h b/gtsam/nonlinear/LevenbergMarquardtOptimizer.h
index f5e4195da..5677f6c08 100644
--- a/gtsam/nonlinear/LevenbergMarquardtOptimizer.h
+++ b/gtsam/nonlinear/LevenbergMarquardtOptimizer.h
@@ -46,13 +46,9 @@ public:
   double lambdaUpperBound; ///< The maximum lambda to try before assuming the optimization has failed (default: 1e5)
   VerbosityLM verbosityLM; ///< The verbosity level for Levenberg-Marquardt (default: SILENT), see also NonlinearOptimizerParams::verbosity
 
-  LevenbergMarquardtParams() :
-    lambdaInitial(1e-5), lambdaFactor(10.0), lambdaUpperBound(1e5), verbosityLM(SILENT) {}
-
-  LevenbergMarquardtParams(double initial, double factor, double bound, size_t verbose) :
-    lambdaInitial(initial), lambdaFactor(factor), lambdaUpperBound(bound), verbosityLM(VerbosityLM(verbose)) {}
-
+  LevenbergMarquardtParams() : lambdaInitial(1e-5), lambdaFactor(10.0), lambdaUpperBound(1e5), verbosityLM(SILENT) {}
   virtual ~LevenbergMarquardtParams() {}
+
   virtual void print(const std::string& str = "") const;
 
   inline double getlambdaInitial() const { return lambdaInitial; }
diff --git a/matlab/examples/SFMExample.m b/matlab/examples/SFMExample.m
index 34682e1e6..277f31648 100644
--- a/matlab/examples/SFMExample.m
+++ b/matlab/examples/SFMExample.m
@@ -63,7 +63,7 @@ initialEstimate.print(sprintf('\nInitial estimate:\n  '));
 
 %% Fine grain optimization, allowing user to iterate step by step
 
-parameters = gtsamLevenbergMarquardtParams(1e-5, 1e-5, 0, 0);
+parameters = gtsamLevenbergMarquardtParams;
 parameters.setlambdaInitial(1.0);
 parameters.setVerbosityLM('trylambda');
 
diff --git a/matlab/tests/testSFMExample.m b/matlab/tests/testSFMExample.m
index ebda9535e..ef27a7e4b 100644
--- a/matlab/tests/testSFMExample.m
+++ b/matlab/tests/testSFMExample.m
@@ -48,7 +48,7 @@ for j=1:size(truth.points,2)
 end
 
 %% Optimization
-parameters = gtsamLevenbergMarquardtParams(1e-5, 1e-5, 0, 0);
+parameters = gtsamLevenbergMarquardtParams;
 optimizer = graph.optimizer(initialEstimate, parameters);
 for i=1:5
     optimizer.iterate();