Boosting Network Weight Separability via Feed-Backward Reconstruction

20 Oct 2019Jongmin YuYounkwan LeeMoongu Jeon

This paper proposes a new evaluation metric and boosting method for weight separability in neural network design. In contrast to general visual recognition methods designed to encourage both intra-class 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... (read more)

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