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Abstract: We provide a variable metric stochastic approximation theory. In doing so, weprovide a convergence theory for a large class of online variable metricmethods including the recently introduced online versions of the BFGS algorithmand its limited-memory LBFGS variant. We also discuss the implications of ourresults for learning from expert advice.



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

Fuente: https://arxiv.org/



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