Documentation update

Change-Id: I0fec43bff4fe0ea6cd2d2a8b34dac2330a517da0

docs/source/modeling.rst

diff --git a/docs/source/modeling.rst b/docs/source/modeling.rst
index c816676..34c3bf8 100644
--- a/docs/source/modeling.rst
+++ b/docs/source/modeling.rst
@@ -1,9 +1,7 @@
 .. default-domain:: cpp
 
-
 .. cpp:namespace:: ceres
 
-
 .. _`chapter-modeling`:
 
 ============
@@ -30,6 +28,15 @@
 that is used to reduce the influence of outliers on the solution of
 non-linear least squares problems.
 
+In this chapter we will describe the various classes that are part of
+Ceres Solver's modeling API, and how they can be used to construct
+optimization.
+
+Once a problem has been constructed, various methods for solving them
+will be discussed in :ref:`chapter-solving`. It is by design that the
+modeling and the solving APIs are orthogonal to each other. This
+enables easy switching/tweaking of various solver parameters without
+having to touch the problem once it has been successfuly modeling.
 
 :class:`CostFunction`
 ---------------------

docs/source/tutorial.rst

diff --git a/docs/source/tutorial.rst b/docs/source/tutorial.rst
index c85e98a..eac50b4 100644
--- a/docs/source/tutorial.rst
+++ b/docs/source/tutorial.rst
@@ -27,7 +27,8 @@
 a scalar function that is used to reduce the influence of outliers on
 the solution of non-linear least squares problems. As a special case,
 when :math:`\rho_i(x) = x`, i.e., the identity function, we get the
-more familiar `non-linear least squares problem` <http:
+more familiar `non-linear least squares problem
+<http://en.wikipedia.org/wiki/Non-linear_least_squares>`_.
 
 .. math:: \frac{1}{2}\sum_{i=1} \left\|f_i\left(x_{i_1}, ... ,x_{i_k}\right)\right\|^2.
    :label: ceresproblem2

docs/source/version_history.rst

diff --git a/docs/source/version_history.rst b/docs/source/version_history.rst
index 6cfb80c..010b477 100644
--- a/docs/source/version_history.rst
+++ b/docs/source/version_history.rst
@@ -15,6 +15,8 @@
    gradient descent, non-linear conjugate gradient and LBFGS search
    directions.
 
+#. New, much improved HTML documentation using Sphinx.
+
 #. Speedup the robust loss function correction logic when residual is
    one dimensional.
 
@@ -23,8 +25,19 @@
 
 #. Added support for mixing automatic, analytic and numeric
    differentiation. This is done by adding ``CostFunctionToFunctor``
-   and ``NumericDiffFunctor`` objects.
+   and ``NumericDiffFunctor`` objects to the API.
 
+#. ``Summary::FullReport`` now reports the structure of the ordering
+   used by the ``LinearSolver`` and inner iterations.
+
+#. Ceres when run at the ``VLOG`` level 3 or higher will report
+   detailed timing information about its internals.
+
+#. Remove extraneous initial and final residual evaluations. This
+   speeds up the solver a bit.
+
+#. Automatic differenatiation with a dynamic number of parameter
+   blocks. (Based on an initial implementation by Thad Hughes).
 
 Bug Fixes
 ---------
@@ -37,6 +50,13 @@
 
 #. Fixed an initialization bug in ``ProgramEvaluator``.
 
+#. Fixes to Android.mk paths (Carlos Hernandez)
+
+#. Modify ``nist.cc`` to compute accuracy based on ground truth
+   solution rather than the ground truth function value.
+
+#. Fixed a memory leak in ``cxsparse.cc``. (Alexander Mordvintsev).
+
 
 1.4.0
 =====

include/ceres/dynamic_autodiff_cost_function.h

diff --git a/include/ceres/dynamic_autodiff_cost_function.h b/include/ceres/dynamic_autodiff_cost_function.h
index 4226177..f2e7c26 100644
--- a/include/ceres/dynamic_autodiff_cost_function.h
+++ b/include/ceres/dynamic_autodiff_cost_function.h
@@ -41,7 +41,7 @@
 //
 //   struct MyCostFunctor {
 //     template<typename T>
-//     bool operator()(const* const* T parameters, T* residuals) const {
+//     bool operator()(T const* const* parameters, T* residuals) const {
 //       // Use parameters[i] to access the i'th parameter block.
 //     }
 //   }