Regularized stochastic BFGS algorithm

A regularized stochastic version of the Broyden-Fletcher- Goldfarb-Shanno (BFGS) quasi-Newton method is proposed to solve optimization problems with stochastic objectives that arise in large scale machine learning. Stochastic gradient descent is the currently preferred solution methodology but the n...

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Vydané v:	2013 IEEE Global Conference on Signal and Information Processing (GlobalSIP) s. 1109 - 1112
Hlavní autori:	Mokhtari, Aryan, Ribeiro, Alejandro
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 01.12.2013
Predmet:	Approximation algorithms Approximation methods Convergence Eigenvalues and eigenfunctions Linear programming Machine learning algorithms Vectors
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