Abstract:This paper proposes a new evaluation metric and a boosting method for weight separability in neural network design. In contrast to general visual recognition methods designed to encourage both intraclass compactness and inter-class separability of latent features, we focus on estimating linear independence of column vectors in weight matrix and improving the separability of weight vectors. To this end, we propose an evaluation metric for weight separability based on semi-orthogonality of a matrix, Frobenius di… Show more
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