wolffd@0: function Xi = lossHingeMKLFull(W, Psi, M, gradient)
wolffd@0: %
wolffd@0: %   Xi = lossHingeMKLFull(W, Psi, M, gradient)
wolffd@0: %   
wolffd@0: %   W:          d*d*m metric
wolffd@0: %   Psi:        d*d*m feature matrix
wolffd@0: %   M:          the desired margin
wolffd@0: %   gradient:   if 0, returns the loss value
wolffd@0: %               if 1, returns the gradient of the loss WRT W
wolffd@0:     
wolffd@0:     m = size(W, 3);
wolffd@0: 
wolffd@0:     Xi = M;
wolffd@0:     for i = 1:m
wolffd@0:         Xi = Xi -  sum(sum(W(:,:,i) .* Psi(:,:,i)));
wolffd@0:     end
wolffd@0:     Xi = max(0, Xi);
wolffd@0: 
wolffd@0:     if gradient & Xi > 0
wolffd@0:         Xi = -Psi;
wolffd@0:     end
wolffd@0: end