diff --git a/doc/whats_new.rst b/doc/whats_new.rst
index 2d2b5138e622e..bfea4448e5958 100644
--- a/doc/whats_new.rst
+++ b/doc/whats_new.rst
@@ -51,6 +51,10 @@ Changelog
      with `decision_function`; for ``kernel==linear``, `coef_` was fixed
      in the the one-vs-one case, by `Andreas Müller`_.
 
+   - Performance improvements to efficient leave-one-out cross-validated
+     Ridge regression, esp. for the ``n_samples > n_features`` case, in
+     :class:`linear_model.RidgeCV`, by Reuben Fletcher-Costin.
+
 
 
 API changes summary
diff --git a/sklearn/linear_model/ridge.py b/sklearn/linear_model/ridge.py
index 1cbda45f8c9f1..4b7f45b28c474 100644
--- a/sklearn/linear_model/ridge.py
+++ b/sklearn/linear_model/ridge.py
@@ -2,9 +2,11 @@
 Ridge regression
 """
 
-# Author: Mathieu Blondel <mathieu@mblondel.org>
+# Author:   Mathieu Blondel <mathieu@mblondel.org>
+#           Reuben Fletcher-Costin <reuben.fletchercostin@gmail.com>
 # License: Simplified BSD
 
+
 import numpy as np
 
 from .base import LinearModel
@@ -501,8 +503,7 @@ class RidgeCV(LinearModel):
     """Ridge regression with built-in cross-validation.
 
     By default, it performs Generalized Cross-Validation, which is a form of
-    efficient Leave-One-Out cross-validation. Currently, only the n_features >
-    n_samples case is handled efficiently.
+    efficient Leave-One-Out cross-validation.
 
     Parameters
     ----------