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Improved Preconditioner for Hessian Free Optimization

2010-10-01NIPS 2010Code Available0· sign in to hype

Olivier Chapelle, Dumitru Erhan

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Abstract

We investigate the use of Hessian Free optimization for learning deep autoencoders. One of the critical components in that algorithm is the choice of the preconditioner. We argue in this paper that the Jacobi preconditioner leads to faster optimization and we show how it can be accurately and efficiently estimated using a randomized algorithm.

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