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	A recursive formulation of limited memory variable metric methods Lukšan, Ladislav ; Vlček, Jan Fulltext: content.csg - PDF Plný tet: 0346100 - PDF Detailed record
	Generalizations of the limited-memory BFGS method based on quasi-product form of update Vlček, Jan ; Lukšan, Ladislav Fulltext: content.csg - PDF Plný tet: v1060-09 - PDF Detailed record
	Transformations enabling to construct limited-memory Broyden class methods Vlček, Jan ; Lukšan, Ladislav Fulltext: content.csg - PDF Plný tet: v1037-08 - PDF Detailed record
	Limited-memory projective variable metric methods for unconstrained minimization Vlček, Jan ; Lukšan, Ladislav Fulltext: content.csg - PDF Plný tet: v1036-08 - PDF Detailed record
	New Class of Limited-Memory Variationally-Derived Variable Metric Methods Vlček, Jan ; Lukšan, Ladislav Fulltext: content.csg - PDF Plný tet: v973-06 - PDF Detailed record
	Additional Properties of Shifted Variable Metric Methods Vlček, Jan ; Lukšan, Ladislav Fulltext: content.csg - PDF Plný tet: v899-04 - PDF Detailed record
	New Variable Metric Methods for Unconstrained Minimization Covering the Large-Scale Case Vlček, Jan ; Lukšan, Ladislav Fulltext: content.csg - PDF Plný tet: v876-02 - PDF Detailed record
	Shifted Variable Metric Methods for Unconstrained Optimization Lukšan, Ladislav ; Vlček, Jan A family of shifted variable metric methods for unconstrained optimization is investigated. These methods form a basis for shifted limited-memory variable metric methods introduced in second contribution in proceedings of SANM 2003. We describe basic properties of these methods, establish their global convergence and give conditions for the superlinear rate of convergence. Their efficiency is demonstrated by using extensive numerical experiments. Detailed record
	New Limited-Memory Variable Metric Methods for Unconstrained Optimization Vlček, Jan ; Lukšan, Ladislav A new family of numerically efficient variable metric or quasi-Newton methods for unconstrained optimizaion is adapted for large-scale optimization. Global convergence of the method can be established for convex sufficiently smooth functions. Some encouraging numerical experience is reported. We refer to our report V-876 for proof and details. Detailed record

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