An averaging method for a committee of special-orthogonal-group machines

The present paper aims at introducing a novel procedure for designing an averaging algorithm for a committee of learning machines under the assumption that the machines share a common parameter-space, namely, the group of special orthogonal matrices SO(p). The averaging procedure inputs the patterns learnt by the machines in the committee and outputs a mean-matrix that represents an average of machines´ patterns. Since the space SO(p) is a curved manifold, averaging does not carry on the usual (Euclidean) meaning and should be designed on the basis of the parameter-space´s geometric properties.