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Variable metric stochastic approximation theory

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Date

2009

Authors

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

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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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https://hdl.handle.net/1885/733798295

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ANU Research Publications

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Journal of Machine Learning Research

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Conference paper

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