Number of found documents: 1593
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Laplacian preconditioning of elliptic PDEs: Localization of the eigenvalues of the discretized operator
Gergelits, Tomáš; Mardal, K.-A.; Nielsen, B. F.; Strakoš, Z.
2019 - English
This contribution represents an extension of our earlier studies on the paradigmatic example of the inverse problem of the diffusion parameter estimation from spatio-temporal measurements of fluorescent particle concentration, see [6, 1, 3, 4, 5]. More precisely, we continue to look for an optimal bleaching pattern used in FRAP (Fluorescence Recovery After Photobleaching), being the initial condition of the Fickian diffusion equation maximizing a sensitivity measure. As follows, we define an optimization problem and we show the special feature (so-called complementarity principle) of the optimal binary-valued initial conditions. Available in digital repository of the ASCR
Laplacian preconditioning of elliptic PDEs: Localization of the eigenvalues of the discretized operator

This contribution represents an extension of our earlier studies on the paradigmatic example of the inverse problem of the diffusion parameter estimation from spatio-temporal measurements of ...

Gergelits, Tomáš; Mardal, K.-A.; Nielsen, B. F.; Strakoš, Z.
Ústav informatiky, 2019

On the Optimal Initial Conditions for an Inverse Problem of Model Parameter Estimation - a Complementarity Principle
Matonoha, Ctirad; Papáček, Š.
2019 - English
This contribution represents an extension of our earlier studies on the paradigmatic example of the inverse problem of the diffusion parameter estimation from spatio-temporal measurements of fluorescent particle concentration, see [6, 1, 3, 4, 5]. More precisely, we continue to look for an optimal bleaching pattern used in FRAP (Fluorescence Recovery After Photobleaching), being the initial condition of the Fickian diffusion equation maximizing a sensitivity measure. As follows, we define an optimization problem and we show the special feature (so-called complementarity principle) of the optimal binary-valued initial conditions. Available in digital repository of the ASCR
On the Optimal Initial Conditions for an Inverse Problem of Model Parameter Estimation - a Complementarity Principle

This contribution represents an extension of our earlier studies on the paradigmatic example of the inverse problem of the diffusion parameter estimation from spatio-temporal measurements of ...

Matonoha, Ctirad; Papáček, Š.
Ústav informatiky, 2019

Nonparametric Bootstrap Techniques for Implicitly Weighted Robust Estimators
Kalina, Jan
2018 - English
The paper is devoted to highly robust statistical estimators based on implicit weighting, which have a potential to find econometric applications. Two particular methods include a robust correlation coefficient based on the least weighted squares regression and the minimum weighted covariance determinant estimator, where the latter allows to estimate the mean and covariance matrix of multivariate data. New tools are proposed allowing to test hypotheses about these robust estimators or to estimate their variance. The techniques considered in the paper include resampling approaches with or without replacement, i.e. permutation tests, bootstrap variance estimation, and bootstrap confidence intervals. The performance of the newly described tools is illustrated on numerical examples. They reveal the suitability of the robust procedures also for non-contaminated data, as their confidence intervals are not much wider compared to those for standard maximum likelihood estimators. While resampling without replacement turns out to be more suitable for hypothesis testing, bootstrapping with replacement yields reliable confidence intervals but not corresponding hypothesis tests. Keywords: robust statistics; econometrics; correlation coefficient; multivariate data Fulltext is available at external website.
Nonparametric Bootstrap Techniques for Implicitly Weighted Robust Estimators

The paper is devoted to highly robust statistical estimators based on implicit weighting, which have a potential to find econometric applications. Two particular methods include a robust correlation ...

Kalina, Jan
Ústav informatiky, 2018

Transforming hierarchical images to program expressions using deep networks
Křen, Tomáš
2018 - English
We present a technique describing how to effectively train a neural network given an image to produce a formal description of the given image. The basic motivation of the proposed technique is an intention to design a new tool for automatic program synthesis capable of transforming sensory data (in our case static image, but generally a phenotype) to a formal code expression (i.e. syntactic tree of a program), such that the code (from evolutionary perspective a genotype) evaluates to a value that is similar to the input data, ideally identical. Our approach is partially based on our technique for generating program expressions in the context of typed functional genetic programming. We present promising results evaluating a simple image description language achieved with a deep network combining convolution encoder of images and recurrent decoder for generating program expressions in the sequential prefix notation and propose possible future applications. Keywords: deep networks; automatic program synthesis; image processing Available in a digital repository NRGL
Transforming hierarchical images to program expressions using deep networks

We present a technique describing how to effectively train a neural network given an image to produce a formal description of the given image. The basic motivation of the proposed technique is an ...

Křen, Tomáš
Ústav informatiky, 2018

How to down-weight observations in robust regression: A metalearning study
Kalina, Jan; Pitra, Zbyněk
2018 - English
Metalearning is becoming an increasingly important methodology for extracting knowledge from a data base of available training data sets to a new (independent) data set. The concept of metalearning is becoming popular in statistical learning and there is an increasing number of metalearning applications also in the analysis of economic data sets. Still, not much attention has been paid to its limitations and disadvantages. For this purpose, we use various linear regression estimators (including highly robust ones) over a set of 30 data sets with economic background and perform a metalearning study over them as well as over the same data sets after an artificial contamination. We focus on comparing the prediction performance of the least weighted squares estimator with various weighting schemes. A broader spectrum of classification methods is applied and a support vector machine turns out to yield the best results. While results of a leave-1-out cross validation are very different from results of autovalidation, we realize that metalearning is highly unstable and its results should be interpreted with care. We also focus on discussing all possible limitations of the metalearning methodology in general. Keywords: metalearning; robust statistics; linear regression; outliers Available at various institutes of the ASCR
How to down-weight observations in robust regression: A metalearning study

Metalearning is becoming an increasingly important methodology for extracting knowledge from a data base of available training data sets to a new (independent) data set. The concept of metalearning is ...

Kalina, Jan; Pitra, Zbyněk
Ústav informatiky, 2018

Detailní simulace proudění, teplot a znečištění vzduchu pro oblast Praha-Dejvice
Resler, Jaroslav; Geletič, Jan; Krč, Pavel; Eben, Kryštof
2018 - Czech
Simulations of Prague quarter Dejvice were performed with newly developed urban climate model PALM-4U based on LES model PALM. The modelling domain has extent 1000 x 800 m and the resolution of the model was 2 m. Two 24 hours episodes were simulated. The summer episode was intended to assess mainly the UHI effects and the winter episode to assess mainly the air quality issues. Two variants were simulated - the current real situation and the scenario with considered new buildings in the area of Victory Square (Vítězné náměstí). Some comments of the ressults are appended at the end of the report. Keywords: PALM; LES; Urban Heat Island; Urban Air Quality; scenarios assessment Available in digital repository of the ASCR
Detailní simulace proudění, teplot a znečištění vzduchu pro oblast Praha-Dejvice

Simulations of Prague quarter Dejvice were performed with newly developed urban climate model PALM-4U based on LES model PALM. The modelling domain has extent 1000 x 800 m and the resolution of the ...

Resler, Jaroslav; Geletič, Jan; Krč, Pavel; Eben, Kryštof
Ústav informatiky, 2018

Web Disinformation Detection - Case Study - Novicok in Czechia
Řimnáč, Martin
2018 - Czech
The paper presents a case study of the propaganda usage on a real cause of double agent Sergei Skripal. The formal model describing statements published in web articles is announced and particular interesting aspects of used disinformation are provided together with the reasons, why the disinformation is published. The paper is aimed at the presentation of the data collection to have been created and provides a brief discussion on the used propaganda techniques. Publikování dezinformací na webu hraje stále větší roli, proto vyvstává otázka, jak takovému obsahu čelit, a nebo na jeho potenciální závadnost alespoň upozornit. Propaganda využívá dezinformací k relativizaci skutečností, jejichž popis se snaží většinou nepřímo zpochybnit. Příspěvek formou případové studie v konkrétní kauze formálně popisuje výroky prezentované v článcích publikovaných na webu a to včetně účelu jejich publikování, všímá si některých zajímavých aspektů prezentovaných dezinformací a hledá model pro jejich popis. Cílem příspěvku je informovat o vznikající datové sadě a ilustrovat základní použité dezinformační techniky včetně důsledků jejich použití. Keywords: Dezinformace; Web; Entropie; Pravděpodobnost Fulltext is available at external website.
Web Disinformation Detection - Case Study - Novicok in Czechia

The paper presents a case study of the propaganda usage on a real cause of double agent Sergei Skripal. The formal model describing statements published in web articles is announced and particular ...

Řimnáč, Martin
Ústav informatiky, 2018

Stav předaných dat a úprava rozdělení vybraných měření 2018
Novák, Jakub; Jiřina, M.; Benešová, Michaela
2018 - Czech
Zpráva se týká stavu předávaných dat a úpravy rozdělení vybraných měření pro rok 2018 v rámci projektu TDD-ČR. Cílem je informovat o aktuálním stavu dat a navrhnout opatření pro zachování reprezentativity celého vzorku. Jsou uvedena kritéria filtrace dat a navrženy postupy pro přerozdělení vybraných měření. Keywords: typový diagram dodávky; TDD; spotřeba plynu; měřicí místa; kritéria; filtrace; náhrady Available on request at various institutes of the ASCR
Stav předaných dat a úprava rozdělení vybraných měření 2018

Zpráva se týká stavu předávaných dat a úpravy rozdělení vybraných měření pro rok 2018 v rámci projektu TDD-ČR. Cílem je informovat o aktuálním stavu dat a navrhnout opatření pro zachování ...

Novák, Jakub; Jiřina, M.; Benešová, Michaela
Ústav informatiky, 2018

Sparse Test Problems for Nonlinear Least Squares
Lukšan, Ladislav; Matonoha, Ctirad; Vlček, Jan
2018 - English
This report contains a description of subroutines which can be used for testing large-scale optimization codes. These subroutines can easily be obtained from the web page http://www.cs.cas.cz/~luksan/test.html. Furthermore, all test problems contained in these subroutines are presented in the analytic form. Keywords: large-scale optimization; least squares; test problems Available in a digital repository NRGL
Sparse Test Problems for Nonlinear Least Squares

This report contains a description of subroutines which can be used for testing large-scale optimization codes. These subroutines can easily be obtained from the web page ...

Lukšan, Ladislav; Matonoha, Ctirad; Vlček, Jan
Ústav informatiky, 2018

Problems for Nonlinear Least Squares and Nonlinear Equations
Lukšan, Ladislav; Matonoha, Ctirad; Vlček, Jan
2018 - English
This report contains a description of subroutines which can be used for testing large-scale optimization codes. These subroutines can easily be obtained from the web page http://www.cs.cas.cz/~luksan/test.html. Furthermore, all test problems contained in these subroutines are presented in the analytic form. Keywords: large-scale optimization; least squares; nonlinear equations,; test problems Available in a digital repository NRGL
Problems for Nonlinear Least Squares and Nonlinear Equations

This report contains a description of subroutines which can be used for testing large-scale optimization codes. These subroutines can easily be obtained from the web page ...

Lukšan, Ladislav; Matonoha, Ctirad; Vlček, Jan
Ústav informatiky, 2018

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