diff --git a/GPy/core/gp.py b/GPy/core/gp.py
index 89313ae2..898c7b58 100644
--- a/GPy/core/gp.py
+++ b/GPy/core/gp.py
@@ -89,7 +89,6 @@ class GP(Model):
             assert mean_function.output_dim == self.output_dim
             self.link_parameter(mean_function)
 
-
         #find a sensible inference method
         logger.info("initializing inference method")
         if inference_method is None:
diff --git a/GPy/core/parameterization/variational.py b/GPy/core/parameterization/variational.py
index 7a58ac5e..f33e7715 100644
--- a/GPy/core/parameterization/variational.py
+++ b/GPy/core/parameterization/variational.py
@@ -176,11 +176,11 @@ class SpikeAndSlabPosterior(VariationalPosterior):
             self.mean.fix(warning=False)
             self.variance.fix(warning=False)
         if group_spike:
-            self.gamma_group = Param("binary_prob_group",binary_prob.mean(axis=0),Logistic(1e-6,1.-1e-6))
+            self.gamma_group = Param("binary_prob_group",binary_prob.mean(axis=0),Logistic(1e-10,1.-1e-10))
             self.gamma = Param("binary_prob",binary_prob, __fixed__)
             self.link_parameters(self.gamma_group,self.gamma)
         else:
-            self.gamma = Param("binary_prob",binary_prob,Logistic(1e-6,1.-1e-6))
+            self.gamma = Param("binary_prob",binary_prob,Logistic(1e-10,1.-1e-10))
             self.link_parameter(self.gamma)
             
     def propogate_val(self):