Stochastic Quasi-Newton Methods for Nonconvex Stochastic Optimization
نویسندگان
چکیده
منابع مشابه
Stochastic Quasi-Newton Methods for Nonconvex Stochastic Optimization
In this paper we study stochastic quasi-Newton methods for nonconvex stochastic optimization, where we assume that noisy information about the gradients of the objective function is available via a stochastic first-order oracle (SFO). We propose a general framework for such methods, for which we prove almost sure convergence to stationary points and analyze its worst-case iteration complexity. ...
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ژورنال
عنوان ژورنال: SIAM Journal on Optimization
سال: 2017
ISSN: 1052-6234,1095-7189
DOI: 10.1137/15m1053141