Generalized BackPropagation, Étude De Cas: Orthogonality

17 Nov 2016Mehrtash HarandiBasura Fernando

This paper introduces an extension of the backpropagation algorithm that enables us to have layers with constrained weights in a deep network. In particular, we make use of the Riemannian geometry and optimization techniques on matrix manifolds to step outside of normal practice in training deep networks, equipping the network with structures such as orthogonality or positive definiteness... (read more)

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