Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/702#discussion_r12460316
--- Diff: docs/mllib-optimization.md ---
@@ -128,10 +128,24 @@ is sampled, i.e. `$|S|=$ miniBatchFraction $\cdot n =
1$`, then the algorithm is
standard SGD. In that case, the step direction depends from the uniformly
random sampling of the
point.
+### Limited-memory BFGS
+[Limited-memory BFGS
(L-BFGS)](http://en.wikipedia.org/wiki/Limited-memory_BFGS) is an optimization
+algorithm in the family of quasi-Newton methods to solve the optimization
problems of the form
+`$\min_{\wv \in\R^d} \; f(\wv)$`. The L-BFGS approximates the objective
function locally as a quadratic
--- End diff --
Either `L-BFGS` or `The L-BFGS method`.
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