Practical Gauss-Newton Optimisation for Deep Learning

ICML 2017 Aleksandar BotevHippolyt RitterDavid Barber

We present an efficient block-diagonal ap- proximation to the Gauss-Newton matrix for feedforward neural networks. Our result- ing algorithm is competitive against state- of-the-art first order optimisation methods, with sometimes significant improvement in optimisation performance... (read more)

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