Publikace
- Networks with Finite VC Dimension: Pro and Contra (2025)
- SOFSEM 2025: Theory and Practice of Computer Science. 50th International Conference on Current Trends in Theory and Practice of Computer Science, SOFSEM 2025, Bratislava, Slovak Republic, January 20–23, 2025, Proceedings, Part II (2025)
- SOFSEM 2025: Theory and Practice of Computer Science. 50th International Conference on Current Trends in Theory and Practice of Computer Science, SOFSEM 2025, Bratislava, Slovak Republic, January 20–23, 2025, Proceedings, Part I (2025)
- RNDr. Věra Kůrková, DrSc. : Těším se, že přijde inspirace, o které ještě nevím (2022)
- Artificial Neural Networks and Machine Learning – ICANN 2019: Text and Time Series. Proceedings, Part IV (2019)
- Artificial Neural Networks and Machine Learning – ICANN 2019: Workshop and Special Sessions. Proceedings (2019)
- Artificial Neural Networks and Machine Learning – ICANN 2019: Image Processing. Proceedings, Part III (2019)
- Artificial Neural Networks and Machine Learning – ICANN 2019: Deep Learning. Proceedings, Part II (2019)
- Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation. Proceedings, Part I (2019)
- Artificial Neural Networks and Machine Learning – ICANN 2018. Proceedings, Part I (2018)
- Artificial Neural Networks and Machine Learning – ICANN 2018. Proceedings, Part III (2018)
- Artificial Neural Networks and Machine Learning – ICANN 2018. Proceedings, Part II (2018)
- Nesvoboda plodí matematiky (Věra Kůrková - matematička) (2016)
- ITAT 2014. Information Technologies - Applications and Theory. Part I (2014)
- ITAT 2014. Information Technologies - Applications and Theory. Part II (2014)
- Representations of Highly-Varying Functions by One-Hidden-Layer Networks (2013)
- Fixed and Variable-Width Gaussian Networks (2012)
- Some Comparisons of Complexity in Dictionary-Based and Linear Computational Models (2011)
- Integral Combinations of Heavisides (2010)
- The 18th International Conference on Artificial Neural Networks, ICANN 2008 (2010)
- Learning as an Inverse Problem in Reproducing Kernel Hilbert Spaces (2010)
- Approximate Minimization of the Regularized Expected Error over Kernel Models (2008)
- An integral upper bound for neural-network approximation (2008)
- Artificial Neural Networks - ICANN 2008. Part II (2008)
- Artificial Neural Networks - ICANN 2008. Part I (2008)
- International Conference on Artificial Neural Networks /18./ (2008)
- Rates of Approximation of Smooth Functions by Gaussian Radial-Basis Networks (2006)
- Integral Combinations of Heavisides (2006)
- Neural Network Learning as an Inverse Problem (2005)
- Supervised Learning as an Inverse Problem (2004)
- A Sobolev-Type Upper Bound for Rates of Approximation by Linear Combinations of Plane Waves (2004)
- Learning with Generalization Capability by Kernel Methods of Bounded Complexity (2003)
- Best Approximation by Linear Combinations of Characteristic Functions of Half-Spaces (2003)
- Minimization of Error Functionals over Variable-basis Functions (2003)
- Minimization of Error Functionals over Variable-Basis Functions (2002)
- Error Estimates for Approximate Optimization by the Extended Ritz Method (2002)
- Tight Bounds on Rates of Variable-Basis Approximation via Estimates of Covering Numbers (2001)
- Artificial Neural Nets and Genetic Algorithms. Proceedings of the International conference (2001)
- Covering Numbers and Rates of Neural-Network Approximation (2001)
- Geometry and Topology of Continuous Best and Near Best Approximations (2000)
- Approximation by Neural Networks is not Continuous (1999)
- Dimension-Independent Approximation by Neural Networks and Its Comparison with Linear Approximation (1999)
- Best Approximation by Linear Combinations of Characteristic Functions of Half-Spaces (1999)
- Aproximace funkcí neuronovými sítěmi (1998)
- Representations and Rates of Approximation of Real-Valued Boolean Functions by Neural Networks (1998)
- Aproximace funkcí neuronovými sítěmi (1998)
- Geometry and Topology of Continuous Best and Near Best Approximations (1998)
- Estimates of the Number of Hidden Units and Variation with Respect to Half-Spaces (1997)
- Trade-off Between the Size of Weights and the Number of Hidden Units in Feedforward Networks (1996)
- Singularities of Finite Scaling Functions (1996)
- Approximation of Functions by Perceptron Networks with Bounded Number of Hidden Units (1995)
- Dimension-Independent Rates of Approximation by Neural Networks and Variation with Respect to Half-spaces (1995)
- Estimates of the Number of Hidden Units and Variation with Respect to Half-Spaces (1995)
- Approximation of Functions by Neural Networks with Local and Non-Local Units (1994)
- Approximation of Functions by Perceptron Networks with Bounded Number of Hidden Units (1994)
- Functionally Equivalent Feedforward Neural Networks (1994)
- Affinely Recursive Functions and Neural Networks (1993)
- Uniqueness of Network Parametrizations and Faster Learning (1993)
- Semigroups of Function Preserving Weight Transformations (1992)
- Quasiorthogonal Sets (1992)
- Kolmogorov's Theorem and Multilayer Neural Networks (1992)
- Jemné uniformní prostory (1979)
