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dc.contributor.authorZhang, Yin
Tapia, Richard
Velazquez, Leticia
dc.date.accessioned 2018-06-18T17:47:33Z
dc.date.available 2018-06-18T17:47:33Z
dc.date.issued 1999-03
dc.identifier.citation Zhang, Yin, Tapia, Richard and Velazquez, Leticia. "On Convergence of Minimization Methods: Attraction, Repulsion and Selection." (1999) https://hdl.handle.net/1911/101917.
dc.identifier.urihttps://hdl.handle.net/1911/101917
dc.description.abstract In this paper, we introduce a rather straightforward but fundamental observation concerning the convergence of the general iteration process. x^(k+1) = x^k - alpha(x^k) [B(x^k)]^(-1) grad­f(x^k) for minimizing a function f(x). We give necessary and sufficient conditions for a stationary point of f(x) to be a point of strong attraction of the iteration process. We will discuss various ramifications of this fundamental result, particularly for nonlinear least squares problems.
dc.format.extent 18 pp
dc.title On Convergence of Minimization Methods: Attraction, Repulsion and Selection
dc.type Technical report
dc.date.note March 1999 (Revised August 1999)
dc.identifier.digital TR99-12
dc.type.dcmi Text


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