diff --git a/gtsam_unstable/nonlinear/ConcurrentBatchFilter.cpp b/gtsam_unstable/nonlinear/ConcurrentBatchFilter.cpp
index 9d83c788a..a309b536e 100644
--- a/gtsam_unstable/nonlinear/ConcurrentBatchFilter.cpp
+++ b/gtsam_unstable/nonlinear/ConcurrentBatchFilter.cpp
@@ -454,12 +454,14 @@ void ConcurrentBatchFilter::marginalize(const FastList<Key>& keysToMove) {
     NonlinearFactorGraph marginalFactors;
     BOOST_FOREACH(Index index, indicesToEliminate) {
       GaussianFactor::shared_ptr gaussianFactor = forest.at(index)->eliminateRecursive(parameters_.getEliminationFunction());
-      LinearContainerFactor::shared_ptr marginalFactor(new LinearContainerFactor(gaussianFactor, ordering_, theta_));
-      marginalFactors.push_back(marginalFactor);
-      // Add the keys associated with the marginal factor to the separator values
-      BOOST_FOREACH(Key key, *marginalFactor) {
-        if(!separatorValues_.exists(key)) {
-          separatorValues_.insert(key, theta_.at(key));
+      if(gaussianFactor->size() > 0) {
+        LinearContainerFactor::shared_ptr marginalFactor(new LinearContainerFactor(gaussianFactor, ordering_, theta_));
+        marginalFactors.push_back(marginalFactor);
+        // Add the keys associated with the marginal factor to the separator values
+        BOOST_FOREACH(Key key, *marginalFactor) {
+          if(!separatorValues_.exists(key)) {
+            separatorValues_.insert(key, theta_.at(key));
+          }
         }
       }
     }
@@ -554,8 +556,10 @@ NonlinearFactorGraph ConcurrentBatchFilter::marginalize(const NonlinearFactorGra
   NonlinearFactorGraph marginalFactors;
   BOOST_FOREACH(Index index, indicesToEliminate) {
     GaussianFactor::shared_ptr gaussianFactor = forest.at(index)->eliminateRecursive(function);
-    LinearContainerFactor::shared_ptr marginalFactor(new LinearContainerFactor(gaussianFactor, ordering, values));
-    marginalFactors.push_back(marginalFactor);
+    if(gaussianFactor->size() > 0) {
+      LinearContainerFactor::shared_ptr marginalFactor(new LinearContainerFactor(gaussianFactor, ordering, values));
+      marginalFactors.push_back(marginalFactor);
+    }
   }
 
   return marginalFactors;
diff --git a/gtsam_unstable/nonlinear/ConcurrentBatchSmoother.cpp b/gtsam_unstable/nonlinear/ConcurrentBatchSmoother.cpp
index ed0db072d..d1c741928 100644
--- a/gtsam_unstable/nonlinear/ConcurrentBatchSmoother.cpp
+++ b/gtsam_unstable/nonlinear/ConcurrentBatchSmoother.cpp
@@ -75,27 +75,19 @@ ConcurrentBatchSmoother::Result ConcurrentBatchSmoother::update(const NonlinearF
   }
   gttoc(augment_system);
 
-  // Reorder the system to ensure efficient optimization (and marginalization) performance
-  gttic(reorder);
-  reorder();
-  gttoc(reorder);
-
-  // Optimize the factors using a modified version of L-M
-  gttic(optimize);
+  factors_.print("factors_");
+  theta_.print("theta_");
   if(factors_.size() > 0) {
+    // Reorder the system to ensure efficient optimization (and marginalization) performance
+    gttic(reorder);
+    reorder();
+    gttoc(reorder);
+
+    // Optimize the factors using a modified version of L-M
+    gttic(optimize);
     result = optimize();
+    gttoc(optimize);
   }
-  gttoc(optimize);
-
-
-  // Moved presync code into the update function. Generally, only one call to smoother.update(*) is performed
-  // between synchronizations, so no extra work is being done. This also allows the presync code to be performed
-  // while the filter is still running (instead of during the synchronization when the filter is paused)
-  gttic(presync);
-  if(separatorValues_.size() > 0) {
-    updateSmootherSummarization();
-  }
-  gttoc(presync);
 
   gttoc(update);
 
@@ -414,8 +406,10 @@ void ConcurrentBatchSmoother::updateSmootherSummarization() {
   // Convert the marginal factors into Linear Container Factors and store
   BOOST_FOREACH(Index index, indicesToEliminate) {
     GaussianFactor::shared_ptr gaussianFactor = forest.at(index)->eliminateRecursive(parameters_.getEliminationFunction());
-    LinearContainerFactor::shared_ptr marginalFactor(new LinearContainerFactor(gaussianFactor, ordering_, theta_));
-    smootherSummarization_.push_back(marginalFactor);
+    if(gaussianFactor->size() > 0) {
+      LinearContainerFactor::shared_ptr marginalFactor(new LinearContainerFactor(gaussianFactor, ordering_, theta_));
+      smootherSummarization_.push_back(marginalFactor);
+    }
   }
 
 }