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- W37469912 abstract "(Received 11 January 2002; Revised 17 May 2002; In final form 15 February 2003)We address in this article the choice of both the step and the curve of the parameter space to be used in the linesearch part of descent algorithms for the minimization of least squares objective functions.Our analysis is based on the curvature of the path of the data space followed during the line search.We define first a new and easy to compute ‘‘maximum curvature step’’, which gives a guaranteed valueto the residual at the next iterate, and satisfies a linear decrease condition with ! ¼ 1=2.Then we optimize the ‘‘worst possible situation’’, by moving from one iterate to the next along a geodesicof the output set.Preliminary numerical comparisons of the proposed algorithm with the Gauss–Newton algorithm arepresented." @default.
- W37469912 created "2016-06-24" @default.
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- W37469912 date "2004-01-01" @default.
- W37469912 modified "2023-09-25" @default.
- W37469912 title "Curvature steps and geodesic moves for nonlinear least squares descent algorithms" @default.
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- W37469912 doi "https://doi.org/10.1080/10682760310001598634a" @default.
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