  This paper extends the idea of Universum learning [18, 19] to regression
problems. We propose new Universum-SVM formulation for regression problems that
incorporates a priori knowledge in the form of additional data samples. These
additional data samples or Universum belong to the same application domain as
the training samples, but they follow a different distribution. Several
empirical comparisons are presented to illustrate the utility of the proposed
approach.
