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<h1> RankNCG </h1>
<a href="FastErfcSummation.html" source="blank">FastErfcSummation</a> Code for fast erfc summation.<br>
<a href="FastErfcSummation_MATLAB.html" source="blank">FastErfcSummation_MATLAB</a> Code for fast erfc summation.<br>
<a href="RankNCG_linear_ranking_function.html" source="blank">RankNCG_linear_ranking_function</a> Implementation of the linear ranking function.<br>
<a href="RankNCG_linear_train.html" source="blank">RankNCG_linear_train</a> Trains a linear ranking function using nonlinear conjugate gradient.<br>
<a href="choose_parameters.html" source="blank">choose_parameters</a> Choose the parameters for fast erfc summation.<br>
<a href="compute_WMW.html" source="blank">compute_WMW</a> Computes the Generalized Wilcoxon-Mann-Whitney Statistic.<br>
<a href="convert_data_to_ranking_format.html" source="blank">convert_data_to_ranking_format</a> Converts the data to a format suitable for my ranking experiments.<br>
<a href="gradient_vector_linear_approx.html" source="blank">gradient_vector_linear_approx</a> This function returns the gradient vecotr to be used by the nonlinear<br>
<a href="gradient_vector_linear_approx_old.html" source="blank">gradient_vector_linear_approx_old</a> This function returns the gradient vecotr to be used by the nonlinear<br>
<a href="gradient_vector_linear_direct.html" source="blank">gradient_vector_linear_direct</a> This function returns the gradient vecotr to be used by the nonlinear<br>
<a href="nonlinear_conjugate_gradient.html" source="blank">nonlinear_conjugate_gradient</a> Minimize a function using nonlinear conjugate gradient with secant and Polak-Ribiere.<br>
<a href="workbench_RankNCG_linear_approx.html" source="blank">workbench_RankNCG_linear_approx</a> <br>
<a href="workbench_RankNCG_linear_direct.html" source="blank">workbench_RankNCG_linear_direct</a> <br>
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