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	A Hybrid Method for Nonlinear Least Squares that Uses Quasi-Newton Updates Applied to an Approximation of the Jacobian Matrix Lukšan, Ladislav ; Vlček, Jan In this contribution, we propose a new hybrid method for minimization of nonlinear least squares. This method is based on quasi-Newton updates, applied to an approximation A of the Jacobian matrix J, such that AT f = JT f. This property allows us to solve a linear least squares problem, minimizing ∥Ad+f∥ instead of solving the normal equation ATAd+JT f = 0, where d ∈ Rn is the required direction vector. Computational experiments confirm the efficiency of the new method. Detailed record
	New Quasi-Newton Method for Solving Systems of Nonlinear Equations Lukšan, Ladislav ; Vlček, Jan Fulltext: content.csg - PDF Plný tet: v1233-16 - PDF Detailed record
	New Subroutines for Large-Scale Optimization Lukšan, Ladislav ; Matonoha, Ctirad ; Vlček, Jan Fulltext: content.csg - PDF Plný tet: v999-07 - PDF Detailed record
	Variable Metric Methods for Unconstrained Optimization Lukšan, Ladislav ; Spedicato, E. ; Vlček, Jan Fulltext: content.csg - PDF Plný tet: v780-99 - PDF Detailed record
	LSA: Algorithms for Large-Scale Optimization Lukšan, Ladislav ; Matonoha, Ctirad ; Vlček, Jan Fulltext: content.csg - PDF Plný tet: v896-04 - PDF Detailed record

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