You are an expert in writing code in many different languages. Your goal is to perform code completion for the following code, keeping in mind the rest of the code and the file meta data.
    Metadata details:
    filename: MAED.m
    path of file: ./repos/MatlabFunc/ActiveLearning
    
    the code of the file until where you have to start completion: function sampleList = MAED(fea,selectNum,options)
% MAED: Manifold Adaptive Experimental Design  
%
%     sampleList = MAED(fea,selectNum,options)
%   
%     Input:
%
%              fea      - Data matrix. Each row of fea is a sample.
%         selectNum     - The number of samples to select.
%           options     - Struct value in Matlab. The fields in options
%                         that can be set:
%
%                splitLabel    -  logical array with the size as the number
%                                 of samples. If some of the inputs already
%                                 have the label and there is no need
%                                 select these samples, you should set the
%                                 corresponding entry in 'splitLabel' as
%                                 true; (Default: all false)
%
%                      W       -  Affinity matrix. You can either call
%                                 "constructW" to construct the W, or
%                                 construct it by yourself.
%                                 If 'W' is not provided and 'ReguBeta'>0 , 
%                                 MAED will build a k-NN graph with Heat kernel
%                                 weight, where 'k' is a prameter. 
%
%                      k       -  The parameter for k-NN graph (Default is 5)
%                                 If 'W' is provided, this parameter will be
%                                 ignored. 
%
%                  ReguBeta    -  regularization paramter for manifold
%                                 adaptive kernel. 
%
%                  ReguAlpha   -  ridge regularization paramter. Default 0.01
%
%
%     Output:
%
%        sampleList     - The index of the sample which should be labeled.
%
%    Examples:
%
%     See: http://www.zjucadcg.cn/dengcai/Data/ReproduceExp.html#MAED
%
%Reference:
%
%   [1] Deng Cai and Xiaofei He, "Manifold Adaptive Experimental Design for
%   Text Categorization", IEEE Transactions on Knowledge and Data
%   Engineering, vol. 24, no. 4, pp. 707-719, 2012.  
%
%   version 2.0 --Jan/2012
%   version 1.0 --Aug/2008 
%
%   Written by Deng Cai (dengcai AT gmail.com)
%



    
function sampleList = MAED(fea,selectNum,options)
% MAED: Manifold Adaptive Experimental Design  
%
%     sampleList = MAED(fea,selectNum,options)
%   
%     Input:
%
%              fea      - Data matrix. Each row of fea is a sample.
%         selectNum     - The number of samples to select.
%           options     - Struct value in Matlab. The fields in options
%                         that can be set:
%
%                splitLabel    -  logical array with the size as the number
%                                 of samples. If some of the inputs already
%                                 have the label and there is no need
%                                 select these samples, you should set the
%                                 corresponding entry in 'splitLabel' as
%                                 true; (Default: all false)
%
%                      W       -  Affinity matrix. You can either call
%                                 "constructW" to construct the W, or
%                                 construct it by yourself.
%                                 If 'W' is not provided and 'ReguBeta'>0 , 
%                                 MAED will build a k-NN graph with Heat kernel
%                                 weight, where 'k' is a prameter. 
%
%                      k       -  The parameter for k-NN graph (Default is 5)
%                                 If 'W' is provided, this parameter will be
%                                 ignored. 
%
%                  ReguBeta    -  regularization paramter for manifold
%                                 adaptive kernel. 
%
%                  ReguAlpha   -  ridge regularization paramter. Default 0.01
%
%
%     Output:
%
%        sampleList     - The index of the sample which should be labeled.
%
%    Examples:
%
%     See: http://www.zjucadcg.cn/dengcai/Data/ReproduceExp.html#MAED
%
%Reference:
%
%   [1] Deng Cai and Xiaofei He, "Manifold Adaptive Experimental Design for
%   Text Categorization", IEEE Transactions on Knowledge and Data
%   Engineering, vol. 24, no. 4, pp. 707-719, 2012.  
%
%   version 2.0 --Jan/2012
%   version 1.0 --Aug/2008 
%
%   Written by Deng Cai (dengcai AT gmail.com)
%


nSmp = size(fea,1);

splitLabel = false(nSmp,1);
if isfield(options,'splitLabel')
    splitLabel = options.splitLabel;
end