A random normal vector is observed in a finite dimensional real vector space E. Its mean is unknown but belongs to a known subspace of E of dimension >3. Its co variance operator is known up to a multiplicative factor. We consider a class of shrinkage estimators of the mean whose shrinkage functions are not necessarily differentiate. We establish a sufficient condition for uniform domination of the maximum likelihood estimator, with respect to an arbitrary quadratic loss.