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	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
	Iterační řešení soustav sedlového bodu: stručný přehled Rozložník, Miroslav In this contribution we attempt to review recent advances in the field of iterative methods for solving large saddle point problems. The main focus is on developments in the area of Krylov subspace methods and block preconditioning techniques for symmetric and nonsymmetric linear systems that arise in the context of solving the saddle point problems. Detailed record

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