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// 
// Nearlest Neighbour Classification for MNIST dataset
//
#include <iostream>
#include <cstdio>
#include <cstdlib>
#include <cmath>
#include <map>
#include <vector>
#include <queue>

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// Read MNIST Database (handwritten digits)
//
// Usage: 
//   1. download 
//        train-images-idx3-ubyte.gz
//        train-labels-idx2-ubyte.gz
//      from
//        http://yann.lecun.com/exdb/mnist/
//      and extract them.
//

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% Radial Basis Function expansion
%
% f(x) = sum k(x, yi) wi 
%   -> w = k(X,Y) \ f(X) 
% here k(x,y) := rho(|x-y|), e.g., exp(-|x-y2|^2)

% input data
N = 100;
X = rand(N,1);
fX = abs( cos( 2 * 3.14 * (X .* X) ) );

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// Two-layer Neural Network
//
// USAGE: 
//   ./a.out in.txt out.txt
//   gnuplot -e "plot 'in.txt', 'out.txt'; pause 2"
//
#include <iostream>
#include <cstdio>
#include <ctime>
#include <cstdlib>

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// 
// Sparse LU Decomposition (Gilbert-Peierls)
//
#include <iostream>
#include <cstdio>
#include <cstdlib>
#include <vector>
#include <functional>
#include <algorithm>
#include <cmath>

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:)