RES: Regularized Stochastic BFGS Algorithm

RES, a regularized stochastic version of the Broyden-Fletcher-Goldfarb-Shanno (BFGS) quasi-Newton method is proposed to solve convex optimization problems with stochastic objectives. The use of stochastic gradient descent algorithms is widespread, but the number of iterations required to approximate...

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Vydané v:	arXiv.org
Hlavní autori:	Mokhtari, Aryan, Ribeiro, Alejandro
Médium:	Paper
Jazyk:	English
Vydavateľské údaje:	Ithaca Cornell University Library, arXiv.org 29.01.2014
Predmet:	Algorithms Approximation Computational efficiency Computational geometry Convergence Convexity Curvature Economic models Mathematical analysis Nonlinear programming Optimization Quasi Newton methods Support vector machines Upper bounds
ISSN:	2331-8422
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