Advanced Search

Query:

Fill in the form and click »Search«...

Format:

Display: entries per page entries

Zbl 0846.90083
Burke, J.V.; Ferris, M.C.
A Gauss-Newton method for convex composite optimization. (English)
[J] Math. Program. 71, No.2 (A), 179-194 (1995). ISSN 0025-5610; ISSN 1436-4646/e

Summary: An extension of the Gauss-Newton method for nonlinear equations to convex composite optimization is described and analyzed. Local quadratic convergence is establised for the minimization of $h\circ F$ under two conditions, namely $h$ has a set of weak sharp minima, $C$, and there is a regular point of the inclusion $F(x)\in C$. This result extends a similar convergence result due to Womersley (1985) which employs the assumption of a strongly unique solution of the composite function $h\circ F$. A backtracking line-search is proposed as a globalization strategy. For this algorithm, a global convergence result is established, with a quadratic rate under the regularity assumption.

MSC 2000:: *90C25 Convex programming

Keywords: weak sharp minima; local quadratic convergence; Gauss-Newton method; convex composite optimization

Cited in: Zbl 1049.90132

Comment on this Item PDF MathML XML ASCII DVI PS BibTeX Online Ordering Article Journal

	Scientific prize winners of the ICM 2010
	Overhang
	Lie groups, physics and geometry. An introduction for physicists, engineers and chemists.

Advanced Search

Zentralblatt MATH Berlin [Germany]