Radial effect in stochastic diagonal approximate greatest descent

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Radial effect in stochastic diagonal approximate greatest descent

© 2017 IEEE. Stochastic Diagonal Approximate Greatest Descent (SDAGD) is proposed to manage the optimization in two stages, (a) apply a radial boundary to estimate step length when the weights are far from solution, (b) apply Newton method when the weights are within the solution level set. This is...

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Bibliographic Details
Main Authors:	Tan, H., Lim, Hann, Harno, H.
Format:	Conference Paper
Published:	2017
Online Access:	http://hdl.handle.net/20.500.11937/65903

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