%
% KERNEL MANIFOLD ALIGNMENT
%
%    This demo illustrates the performance of the semisupervised kernel 
%    manifold alignment (KEMA) in several toy examples.
%
%   All these programs included in this package are intended for illustration
%   purposes and as accompanying software for the paper:
%
%           Devis Tuia and Gustau Camps-Valls. 
%           "Kernel Manifold Alignment for Domain Adaptation". PLoS One, 2016
%
%   If you find the software useful in other domains, we would greatly 
%   acknowledge 
%   citing our paper above. Also, please consider citing these papers:
%
%        Semisupervised Manifold Alignment of Multimodal Remote Sensing Images
%            Devis Tuia, Michele Volpi, Maxime Trolliet, and G. Camps-Valls
%            IEEE Transactions on Geoscience and Remote Sensing, 52(12), 7708-7720, Dec. 2014
%
%        Unsupervised Alignment of Image Manifolds with Centrality Measures
%            Devis Tuia, Michele Volpi and G. Camps-Valls
%            22nd International Conference on Pattern Recognition, ICPR 2014
%            Stockholm, Sweden, August 2014
%
%   --------------------------------------
%   Copyright & Disclaimer
%   --------------------------------------
%
%   The programs contained in this package are granted free of charge for
%   research and education purposes only. Scientific results produced using
%   the software provided shall acknowledge the use of this implementation
%   provided by us. If you plan to use it for non-scientific purposes,
%   don't hesitate to contact us. Because the programs are licensed free of
%   charge, there is no warranty for the program, to the extent permitted
%   by applicable law. except when otherwise stated in writing the
%   copyright holders and/or other parties provide the program "as is"
%   without warranty of any kind, either expressed or implied, including,
%   but not limited to, the implied warranties of merchantability and
%   fitness for a particular purpose. the entire risk as to the quality and
%   performance of the program is with you. should the program prove
%   defective, you assume the cost of all necessary servicing, repair or
%   correction. In no event unless required by applicable law or agreed to
%   in writing will any copyright holder, or any other party who may modify
%   and/or redistribute the program, be liable to you for damages,
%   including any general, special, incidental or consequential damages
%   arising out of the use or inability to use the program (including but
%   not limited to loss of data or data being rendered inaccurate or losses
%   sustained by you or third parties or a failure of the program to
%   operate with any other programs), even if such holder or other party
%   has been advised of the possibility of such damages.
%
%   NOTE: This is just a demo providing a default initialization. Training
%   is not at all optimized. Other initializations, optimization techniques, 
%   and training strategies may be of course better suited to achieve improved 
%   results in this or other problems. We just did it in the standard way for 
%   illustration purposes and dissemination of these models. 
%
% Copyright (c) 2015 by Devis Tuia and Gustau Camps-Valls
%
%      Devis Tuia, <devis.tuia@geo.uzh.ch> 
%      University of Zurich, Switzerland 
%      http://www.geo.uzh.ch/en/units/multimodal-remote-sensing
%
%      Gustau Camps-Valls, <gustau.camps@uv.es>, 
%      Universitat de Valencia, Spain
%      http://isp.uv.es/
%