wolffd@0: function D = setDistanceFullMKL(X, W, Ifrom, Ito)
wolffd@0: %
wolffd@0: % D = setDistanceFullMKL(X, W, Ifrom, Ito)
wolffd@0: %
wolffd@0: %   X       = d-by-n-by-m data matrix
wolffd@0: %   W       = d-by-d-by-m PSD matrix
wolffd@0: %   Ifrom   = k-by-1 vector of source points
wolffd@0: %   Ito     = j-by-1 vector of destination points
wolffd@0: %
wolffd@0: %   D = n-by-n matrix of squared euclidean distances from Ifrom to Ito
wolffd@0: %       D is sparse, and only the rows corresponding to Ifrom and
wolffd@0: %       columns corresponding to Ito are populated.
wolffd@0: 
wolffd@0:     [d,n,m]       = size(X);
wolffd@0: 
wolffd@0:     D = 0;
wolffd@0: 
wolffd@0:     if nargin < 4
wolffd@0:         Ito     = 1:n;
wolffd@0:     end
wolffd@0: 
wolffd@0:     parfor i = 1:m
wolffd@0:         [vecs,vals] = eig(0.5 * (W(:,:,i) + W(:,:,i)'));
wolffd@0:         L           = real(abs(vals)).^0.5 * vecs';
wolffd@0: 
wolffd@0:         Vfrom   = L * X(:,Ifrom,i);
wolffd@0: 
wolffd@0:         Vto     = L * X(:,Ito,i);
wolffd@0: 
wolffd@0:         D = D + distToFrom(n, Vto, Vfrom, Ito, Ifrom);
wolffd@0:     end
wolffd@0: end