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Commit 10bd680f authored by Davis King's avatar Davis King
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updated docs

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docs/docs/optimization.xml
View file @ 10bd680f
......@@ -27,10 +27,12 @@
<section>
<name>General Purpose Optimizers</name>
<item>find_min</item>
<item>find_min_box_constrained</item>
<item>find_min_single_variable</item>
<item>find_min_using_approximate_derivatives</item>
<item>find_min_bobyqa</item>
<item>find_max</item>
<item>find_max_box_constrained</item>
<item>find_max_single_variable</item>
<item>find_max_using_approximate_derivatives</item>
<item>find_max_bobyqa</item>
......@@ -71,10 +73,12 @@
<name>Helper Routines</name>
<item>derivative</item>
<item>negate_function</item>
<item>clamp_function</item>
<item>make_line_search_function</item>
<item>poly_min_extrap</item>
<item>lagrange_poly_min_extrap</item>
<item>line_search</item>
<item>backtracking_line_search</item>
<item>graph_cut_score</item>
<item>potts_model_score</item>
<item>parse_tree_to_string</item>
......@@ -118,6 +122,21 @@
</component>
<!-- ************************************************************************* -->
<component>
<name>clamp_function</name>
<file>dlib/optimization.h</file>
<spec_file link="true">dlib/optimization/optimization_abstract.h</spec_file>
<description>
This is a function that takes another function, f(x), as input and
returns a new function object, g(x), such that
<tt>g(x) == f(clamp(x,x_lower,x_upper))</tt> where x_lower and x_upper
are vectors of box constraints which are applied to x.
</description>
</component>
<!-- ************************************************************************* -->
<component>
......@@ -128,7 +147,8 @@
This is a function that takes another function f(x) as input and returns
a function object l(z) = f(start + z*direction). It is useful for
turning multi-variable functions into single-variable functions for
use with the <a href="#line_search">line_search</a> routine.
use with the <a href="#line_search">line_search</a> or
<a href="#backtracking_line_search">backtracking_line_search</a> routines.
</description>
</component>
......@@ -168,12 +188,28 @@
<spec_file link="true">dlib/optimization/optimization_line_search_abstract.h</spec_file>
<description>
Performs a gradient based line search on a given function and returns the input
that makes the function significantly smaller.
that makes the function significantly smaller. This implements the classic
line search method using the strong Wolfe conditions with a bracketing and then
sectioning phase, both using polynomial interpolation.
</description>
</component>
<!-- ************************************************************************* -->
<component>
<name>backtracking_line_search</name>
<file>dlib/optimization.h</file>
<spec_file link="true">dlib/optimization/optimization_line_search_abstract.h</spec_file>
<description>
Performs a line search on a given function and returns the input
that makes the function significantly smaller. This implementation uses a
basic Armijo backtracking search with polynomial interpolation.
</description>
</component>
<!-- ************************************************************************* -->
<component>
......@@ -325,6 +361,18 @@
</component>
<!-- ************************************************************************* -->
<component>
<name>find_min_box_constrained</name>
<file>dlib/optimization.h</file>
<spec_file link="true">dlib/optimization/optimization_abstract.h</spec_file>
<description>
Performs a box constrained minimization of a nonlinear function using
some search strategy (e.g. <a href="#bfgs_search_strategy">bfgs_search_strategy</a>).
</description>
</component>
<!-- ************************************************************************* -->
<component>
......@@ -861,6 +909,19 @@ However, for graphs with cycles, the solution may be approximate.
</component>
<!-- ************************************************************************* -->
<component>
<name>find_max_box_constrained</name>
<file>dlib/optimization.h</file>
<spec_file link="true">dlib/optimization/optimization_abstract.h</spec_file>
<description>
Performs a box constrained maximization of a nonlinear function using
some search strategy (e.g. <a href="#bfgs_search_strategy">bfgs_search_strategy</a>).
</description>
</component>
<!-- ************************************************************************* -->
<component>
......
docs/docs/term_index.xml
View file @ 10bd680f
......@@ -100,7 +100,10 @@
<term file="optimization.html" name="poly_min_extrap" include="dlib/optimization.h"/>
<term file="optimization.html" name="lagrange_poly_min_extrap" include="dlib/optimization.h"/>
<term file="optimization.html" name="line_search" include="dlib/optimization.h"/>
<term file="optimization.html" name="backtracking_line_search" include="dlib/optimization.h"/>
<term file="optimization.html" name="find_min" include="dlib/optimization.h"/>
<term file="optimization.html" name="find_min_box_constrained" include="dlib/optimization.h"/>
<term file="optimization.html" name="find_max_box_constrained" include="dlib/optimization.h"/>
<term file="optimization.html" name="max_cost_assignment" include="dlib/optimization.h"/>
<term link="optimization.html#max_cost_assignment" name="Hungarian Algorithm" include="dlib/optimization.h"/>
<term file="optimization.html" name="max_sum_submatrix" include="dlib/optimization.h"/>
......@@ -150,6 +153,7 @@
<term file="optimization.html" name="objective_delta_stop_strategy" include="dlib/optimization.h"/>
<term file="optimization.html" name="gradient_norm_stop_strategy" include="dlib/optimization.h"/>
<term file="optimization.html" name="negate_function" include="dlib/optimization.h"/>
<term file="optimization.html" name="clamp_function" include="dlib/optimization.h"/>
<term file="optimization.html" name="cg_search_strategy" include="dlib/optimization.h"/>
<term file="optimization.html" name="bfgs_search_strategy" include="dlib/optimization.h"/>
<term file="optimization.html" name="newton_search_strategy" include="dlib/optimization.h"/>
......
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