Katerina Hlavácková-Schindler - researchr alias

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Viewing Publication 1 - 25 from 25

2023

Causal Inference for Heterogeneous Data and Information TheoryKaterina Hlavácková-Schindler. entropy, 25(6):910, June 2023. [doi]

2022

2020

2019

Granger Causality for Heterogeneous ProcessesSahar Behzadi, Katerina Hlavácková-Schindler, Claudia Plant. pakdd 2019: 463-475 [doi]

2017

Dependency Anomaly Detection for Heterogeneous Time Series: A Granger-Lasso ApproachSahar Behzadi, Katerina Hlavácková-Schindler, Claudia Plant. icdm 2017: 1090-1099 [doi]

2015

Lasso Granger Causal Models: Some Strategies and Their Efficiency for Gene Expression Regulatory NetworksKaterina Hlavácková-Schindler, Sergiy Pereverzyev Jr.. In Tatiana V. Guy, Miroslav Kárný, David H. Wolpert, editors, Decision Making: Uncertainty, Imperfection, Deliberation and Scalability. Volume 538 of Studies in Computational Intelligence, pages 91-117, Springer, 2015. [doi]

2013

Graphical Lasso Granger Method with 2-Levels-Thresholding for Recovering Causality NetworksSergiy Pereverzyev Jr., Katerina Hlavácková-Schindler. ifip7 2014: 220-229 [doi]

2008

Tikhonov Regularization Parameter in Reproducing Kernel Hilbert Spaces with Respect to the Sensitivity of the SolutionKaterina Hlavácková-Schindler. icann 2008: 215-224 [doi]

2007

Computational Intelligence approaches to causality detectionKaterina Hlavácková-Schindler, Pablo F. Verdes. esann 2007: 433-440 [doi]

Mutual Information Estimation in Higher Dimensions: A Speed-Up of a ::::k:::: -Nearest Neighbor Based EstimatorMartin Vejmelka, Katerina Hlavácková-Schindler. icannga 2007: 790-797 [doi]

2001

Fitting of a closed planar curve representing a profile of an archaeological fragmentKaterina Hlavácková-Schindler, Martin Kampel, Robert Sablatnig. vast 2001: 263-270 [doi]

2000

An Incremental Algorithm for Parallel Training of the Size and the Weights in a Feedforward Neural NetworkKaterina Hlavácková-Schindler, Manfred M. Fischer. npl, 11(2):131-138, 2000.

1999

Some Comparisons Between Linear Approximation and Approximation by Neural NetworksMarcello Sanguineti, Katerina Hlavácková-Schindler. icannga 1999: 172-177 [doi]

1998

Algorithm of Incremental Approximation Using Variation of a Function with Respect to a SubsetKaterina Hlavácková-Schindler, Marcello Sanguineti. nc 1998: 896-899

Representations and rates of approximation of real-valued Boolean functions by neural networksVera Kurková, Petr Savický, Katerina Hlavácková-Schindler. NN, 11(4):651-659, 1998. [doi]

1997

Placing spline knots in neural networks using splines as activation functionsKaterina Hlavácková-Schindler, Michel Verleysen. ijon, 17(3-4):159-166, 1997. [doi]

1996

Rates of approximation of real-valued boolean functions by neural networksKaterina Hlavácková-Schindler, Vera Kurková. esann 1996: [doi]

1995

An upper estimate of the error of approximation of continuous multivariable functions by KBF networksKaterina Hlavácková-Schindler. esann 1995: [doi]

1994

Approximation of continuous functions by RBF and KBF networksVera Kurková, Katerina Hlavácková-Schindler. esann 1994: [doi]

An optimized RBF network for approximation of functionsMichel Verleysen, Katerina Hlavácková-Schindler. esann 1994: [doi]

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