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We study the natural gradient approach to blind separation of overdetermined mixtures. First we introduce a Lie group on the manifold of overdetermined mixtures, and endow a Riemannian metric on the manifold based on the property of the Lie group. Then we derive the natural gradient on the manifold using the isometry of the Riemannian metric. Using the natural gradient, we present a new learning algorithm based on the minimization of mutual information.