diff --git a/gtsam/slam/JacobianFactorSVD.h b/gtsam/slam/JacobianFactorSVD.h
index e5e39d1a1..0b0d76fda 100644
--- a/gtsam/slam/JacobianFactorSVD.h
+++ b/gtsam/slam/JacobianFactorSVD.h
@@ -63,7 +63,7 @@ public:
       QF.push_back(
           KeyMatrix(it.first,
               (Enull.transpose()).block(0, ZDim * j++, m2, ZDim) * it.second));
-    JacobianFactor::fillTerms(QF, Enull.transpose() * b, model);
+    JacobianFactor::fillTerms(QF, - Enull.transpose() * b, model);
   }
 };
 
diff --git a/gtsam/slam/RegularImplicitSchurFactor.h b/gtsam/slam/RegularImplicitSchurFactor.h
index 88fb4b6e1..fd1a5764d 100644
--- a/gtsam/slam/RegularImplicitSchurFactor.h
+++ b/gtsam/slam/RegularImplicitSchurFactor.h
@@ -128,7 +128,7 @@ public:
    * Do Schur complement, given Jacobian as F,E,P, return SymmetricBlockMatrix
    * Fast version - works on with sparsity
    */
-  static void sparseSchurComplement(const std::vector<KeyMatrix2D>& Fblocks,
+  static void SparseSchurComplement(const std::vector<KeyMatrix2D>& Fblocks,
       const Matrix& E, const Matrix3& P /*Point Covariance*/, const Vector& b,
       /*output ->*/SymmetricBlockMatrix& augmentedHessian) {
     // Schur complement trick
@@ -167,7 +167,7 @@ public:
    * Applies Schur complement (exploiting block structure) to get a smart factor on cameras,
    * and adds the contribution of the smart factor to a pre-allocated augmented Hessian.
    */
-  static void updateSparseSchurComplement(
+  static void UpdateSparseSchurComplement(
       const std::vector<KeyMatrix2D>& Fblocks, const Matrix& E,
       const Matrix3& P /*Point Covariance*/, const Vector& b, const double f,
       const FastVector<Key>& allKeys, const FastVector<Key>& keys,
@@ -248,7 +248,7 @@ public:
     SymmetricBlockMatrix augmentedHessian(dims, Matrix::Zero(M1, M1));
 
     // Do the Schur complement
-    sparseSchurComplement(Fblocks_, E_, PointCovariance_, b_, augmentedHessian);
+    SparseSchurComplement(Fblocks_, E_, PointCovariance_, b_, augmentedHessian);
     return augmentedHessian.matrix();
   }
 
@@ -257,7 +257,7 @@ public:
     Matrix augmented = augmentedInformation();
     int m = this->keys_.size();
     size_t M = D * m;
-    return augmented.block(0,0,M,M);
+    return augmented.block(0, 0, M, M);
   }
 
   /// Return the diagonal of the Hessian for this factor
diff --git a/gtsam/slam/SmartFactorBase.h b/gtsam/slam/SmartFactorBase.h
index c9421e173..60e939a89 100644
--- a/gtsam/slam/SmartFactorBase.h
+++ b/gtsam/slam/SmartFactorBase.h
@@ -272,7 +272,7 @@ public:
       EtE.diagonal() += lambda * EtE.diagonal();
     } else {
       DenseIndex n = E.cols();
-      EtE += lambda * Eigen::MatrixXd::Identity(n,n);
+      EtE += lambda * Eigen::MatrixXd::Identity(n, n);
     }
 
     return (EtE).inverse();
@@ -342,7 +342,8 @@ public:
     SymmetricBlockMatrix augmentedHessian(dims, Matrix::Zero(M1, M1));
 
     // build augmented hessian
-    sparseSchurComplement(Fblocks, E, P, b, augmentedHessian);
+    RegularImplicitSchurFactor<Dim>::SparseSchurComplement(Fblocks, E, P, b,
+        augmentedHessian);
     augmentedHessian(m, m)(0, 0) = f;
 
     return boost::make_shared<RegularHessianFactor<Dim> >(keys_,
@@ -363,7 +364,7 @@ public:
     std::vector<KeyMatrix2D> Fblocks;
     double f = computeJacobians(Fblocks, E, b, cameras, point);
     Matrix3 P = PointCov(E, lambda, diagonalDamping);
-    RegularImplicitSchurFactor<Dim, ZDim>::updateSparseSchurComplement(Fblocks,
+    RegularImplicitSchurFactor<Dim, ZDim>::UpdateSparseSchurComplement(Fblocks,
         E, P, b, f, allKeys, keys_, augmentedHessian);
   }
 
@@ -420,7 +421,8 @@ public:
     const size_t M = ZDim * m;
     Matrix E0(M, M - 3);
     computeJacobiansSVD(F, E0, b, cameras, point);
-    SharedIsotropic n = noiseModel::Isotropic::Sigma(M-3, noiseModel_->sigma());
+    SharedIsotropic n = noiseModel::Isotropic::Sigma(M - 3,
+        noiseModel_->sigma());
     return boost::make_shared<JacobianFactorSVD<Dim, ZDim> >(F, E0, b, n);
   }