A Reduction Theorem for Absolute Value Equations
Rohn, Jiří
2014 - English Keywords: absolute value equation; size reduction; solvability Available in a digital repository NRGL A Reduction Theorem for Absolute Value Equations

Rohn, Jiří
Ústav informatiky, 2014

UFO 2013 Interactive System for Universal Functional Optimization.
Lukšan, Ladislav; Tůma, Miroslav; Vlček, Jan; Ramešová, Nina; Šiška, M.; Matonoha, Ctirad; Hartman, J.
2014 - English Keywords: numerical optimization; nonlinear programming; nonlinear approximation; algorithms; software systems Available in a digital repository NRGL UFO 2013 Interactive System for Universal Functional Optimization.

Lukšan, Ladislav; Tůma, Miroslav; Vlček, Jan; Ramešová, Nina; Šiška, M.; Matonoha, Ctirad; Hartman, J.
Ústav informatiky, 2014

Fuzzified linear orderings, fuzzy maxima and minima
Běhounek, Libor
2014 - English Keywords: fuzzy relation; similarity relation; fuzzy ordering; fuzzy maximum; higher-order fuzzy logic Available in a digital repository NRGL Fuzzified linear orderings, fuzzy maxima and minima

Běhounek, Libor
Ústav informatiky, 2014

Kernel density estimates in particle filter
Coufal, David
2014 - English Keywords: particle filters; kernel methods; Fourier analysis Available in a digital repository NRGL Kernel density estimates in particle filter

Coufal, David
Ústav informatiky, 2014

UFO 2014. Interactive System for Universal Functional Optimization
Lukšan, Ladislav; Tůma, Miroslav; Matonoha, Ctirad; Vlček, Jan; Ramešová, Nina; Šiška, M.; Hartman, J.
2014 - English Keywords: numerical optimization; nonlinear programming; nonlinear approximation; algorithms; software systems Available in a digital repository NRGL UFO 2014. Interactive System for Universal Functional Optimization

Lukšan, Ladislav; Tůma, Miroslav; Matonoha, Ctirad; Vlček, Jan; Ramešová, Nina; Šiška, M.; Hartman, J.
Ústav informatiky, 2014

Important Markov-Chain Properties of (1,lambda)-ES Linear Optimization Models
Chotard, A.; Holeňa, Martin
2014 - English Several recent publications investigated Markov-chain modelling of linear optimization by a (1,lambda)-ES, considering both unconstrained and linearly constrained optimization, and both constant and varying step size. All of them assume normality of the involved random steps. This is a very strong and specific assumption. The objective of our contribution is to show that in the constant step size case, valuable properties of the Markov chain can be obtained even for steps with substantially more general distributions. Several results that have been previously proved using the normality assumption are proved here in a more general way without that assumption. Finally, the decomposition of a multidimensional distribution into its marginals and the copula combining them is applied to the new distributional assumptions, particular attention being paid to distributions with Archimedean copulas. Keywords: evolution strategies; random steps; linear optimization; Markov chain models; Archimedean copulas Available in digital repository of the ASCR Important Markov-Chain Properties of (1,lambda)-ES Linear Optimization Models

Several recent publications investigated Markov-chain modelling of linear optimization by a (1,lambda)-ES, considering both unconstrained and linearly constrained optimization, and both constant and ...

Chotard, A.; Holeňa, Martin
Ústav informatiky, 2014

Robustness of High-Dimensional Data Mining
Kalina, Jan; Duintjer Tebbens, Jurjen; Schlenker, Anna
2014 - English Standard data mining procedures are sensitive to the presence of outlying measurements in the data. This work has the aim to propose robust versions of some existing data mining procedures, i.e. methods resistant to outliers. In the area of classification analysis, we propose a new robust method based on a regularized version of the minimum weighted covariance determinant estimator. The method is suitable for data with the number of variables exceeding the number of observations. The method is based on implicit weights assigned to individual observations. Our approach is a unique attempt to combine regularization and high robustness, allowing to downweight outlying high-dimensional observations. Classification performance of new methods and some ideas concerning classification analysis of high-dimensional data are illustrated on real raw data as well as on data contaminated by severe outliers. Keywords: classification analysis; robust estimation; high-dimensional data Available in digital repository of the ASCR Robustness of High-Dimensional Data Mining

Standard data mining procedures are sensitive to the presence of outlying measurements in the data. This work has the aim to propose robust versions of some existing data mining procedures, i.e. ...

Kalina, Jan; Duintjer Tebbens, Jurjen; Schlenker, Anna
Ústav informatiky, 2014

A Class of Explicitly Solvable Absolute Value Equations
Rohn, Jiří
2014 - English Keywords: absolute value equation; solution; explicit form Available in a digital repository NRGL A Class of Explicitly Solvable Absolute Value Equations

Rohn, Jiří
Ústav informatiky, 2014

Explicit Form of Matrices Qz for an Interval Matrix with Unit Midpoint
Rohn, Jiří
2014 - English Keywords: interval matrix; Qz matrix; unit midpoint; explicit formula Available in a digital repository NRGL Explicit Form of Matrices Qz for an Interval Matrix with Unit Midpoint

Rohn, Jiří
Ústav informatiky, 2014

A posteriori algebraic error estimation in numerical solution of linear diffusion PDEs
Papež, Jan; Vohralík, M.
2014 - English Keywords: finite element method; algebraic error; a posteriori error estimation; stopping criteria Available in a digital repository NRGL A posteriori algebraic error estimation in numerical solution of linear diffusion PDEs

Papež, Jan; Vohralík, M.
Ústav informatiky, 2014