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Variable Metric Stochastic Approximation Theory

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Authors

Sunehag, Peter
Trumpf, Jochen
Vishwanathan, S.V.N.
Schraudolph, Nic

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Society for Artificial Intelligence and Statistics

Abstract

We provide a variable metric stochastic approximation theory. In doing so, we provide a convergence theory for a large class of online variable metric methods including the recently introduced online versions of the BFGS algorithm and its limited-memory LBFGS variant. We also discuss the implications of our results for learning from expert advice.

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Citation

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Proceedings of International Conference on Artificial Intelligence and Statistics (AISTATS 2009)

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