Number of found documents: 1162
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Robust Regularized Cluster Analysis for High-Dimensional Data
Kalina, Jan; Vlčková, Katarína
2014 - English
This paper presents new approaches to the hierarchical agglomerative cluster analysis for high-dimensional data. First, we propose a regularized version of the hierarchical cluster analysis for categorical data with a large number of categories. It exploits a regularized version of various test statistics of homogeneity in contingency tables as the measure of distance between two clusters. Further, our aim is cluster analysis of continuous data with a large number of variables. Various regularization techniques tailor-made for high-dimensional data have been proposed, which have however turned out to suffer from a high sensitivity to the presence of outlying measurements in the data. As a robust solution, we recommend to combine two newly proposed methods, namely a regularized version of robust principal component analysis and a regularized Mahalanobis distance, which is based on an asymptotically optimal regularization of the covariance matrix. We bring arguments in favor of the newly proposed methods. Keywords: cluster analysis; robust data mining; big data; regularization Available at various institutes of the ASCR
Robust Regularized Cluster Analysis for High-Dimensional Data

This paper presents new approaches to the hierarchical agglomerative cluster analysis for high-dimensional data. First, we propose a regularized version of the hierarchical cluster analysis for ...

Kalina, Jan; Vlčková, Katarína
Ústav informatiky, 2014

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

ITAT 2014. Information Technologies - Applications and Theory. Part II
Kůrková, Věra; Bajer, Lukáš; Peška, L.; Vojtáš, P.; Holeňa, Martin; Nehéz, M.
2014 - English
ITAT 2014. Information Technologies - Applications and Theory. Part II. Prague : Institute of Computer Science AS CR, 2014. 145 p. ISBN 978-80-87136-19-5. This volume is the second part of the two-volume proceedings of the 14th conference Information Technologies – Applications and Theory (ITAT 2014), which was held in Jasná, Demänovská Dolina, Slovakia, on September 25–29, 2014. ITAT is a computer science conference with the primary goal of exchanging information on recent research results. Overall, 51 papers were submitted to all conference tracks. This volume presents papers from the workshops and an extended abstract of a poster. Three specialized workshops were held as a part of the conference: Data Mining and Preference Learning on Web, Computational Intelligence and Data Mining, and Algorithmic Aspects of Complex Networks Analysis. Keywords: computer science; machine-learning; computer linguistics; data-mining; bio-informatics; parallel processing Available on request at various institutes of the ASCR
ITAT 2014. Information Technologies - Applications and Theory. Part II

ITAT 2014. Information Technologies - Applications and Theory. Part II. Prague : Institute of Computer Science AS CR, 2014. 145 p. ISBN 978-80-87136-19-5. This volume is the second part of the ...

Kůrková, Věra; Bajer, Lukáš; Peška, L.; Vojtáš, P.; Holeňa, Martin; Nehéz, M.
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

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