LBSGD documentation fix

python/mxnet/optimizer/optimizer.py

@@ -686,8 +686,11 @@ class LBSGD(Optimizer):
         state = momentum * state + lr * rescale_grad * clip(grad, clip_gradient) + wd * weight
         weight = weight - state
 
-    For details of the update algorithm see :class:`~mxnet.ndarray.lbsgd_update` and
-    :class:`~mxnet.ndarray.lbsgd_mom_update`.
+    For details of the update algorithm see :class:`~mxnet.ndarray.sgd_update`
+    and :class:`~mxnet.ndarray.sgd_mom_update`.
+    In addition to the SGD updates the LBSGD optimizer uses the LARS, Layer-wise
+    Adaptive Rate Scaling, algorithm to have a separate learning rate for each
+    layer of the network, which leads to better stability over large batch sizes.
 
     This optimizer accepts the following parameters in addition to those accepted
     by :class:`.Optimizer`.