Vera Kurková

Publication Activity (10 Years)

Years Active: 1991-2023
Publications (10 Years): 19

Top Topics

Top Venues

Neural Comput. Appl.

Neural Networks

IEEE Trans. Neural Networks Learn. Syst.

Publications

Vera Kurková, Marcello Sanguineti
Approximation of classifiers by deep perceptron networks. Neural Networks 165 (2023)
Vera Kurková, David Coufal
Translation-Invariant Kernels for Multivariable Approximation. IEEE Trans. Neural Networks Learn. Syst. 32 (11) (2021)
Vera Kurková, Marcello Sanguineti
Correlations of random classifiers on large data sets. Soft Comput. 25 (19) (2021)
Paul C. Kainen, Vera Kurková, Andrew Vogt
Approximative compactness of linear combinations of characteristic functions. J. Approx. Theory 257 (2020)
Lazaros S. Iliadis, Vera Kurková, Barbara Hammer
Brain-inspired computing and machine learning. Neural Comput. Appl. 32 (11) (2020)
Vera Kurková
Limitations of shallow networks representing finite mappings. Neural Comput. Appl. 31 (6) (2019)
Vera Kurková, Marcello Sanguineti
Classification by Sparse Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 30 (9) (2019)
Vera Kurková
Probabilistic Bounds for Approximation by Neural Networks. ICANN (1) (2019)
Vera Kurková
Limitations of Shallow Networks. INNSBDDL (Tutorials) (2019)
Vera Kurková, Marcello Sanguineti
Probabilistic Bounds for Binary Classification of Large Data Sets. INNSBDDL (2019)
Vera Kurková, Marcello Sanguineti
Probabilistic Bounds on Complexity of Networks Computing Binary Classification Tasks. ITAT (2018)
Vera Kurková
Constructive lower bounds on model complexity of shallow perceptron networks. Neural Comput. Appl. 29 (7) (2018)
Vera Kurková
Sparsity and Complexity of Networks Computing Highly-Varying Functions. ICANN (3) (2018)
Vera Kurková
Sparsity of Shallow Networks Representing Finite Mappings. EANN (2017)
Vera Kurková, Marcello Sanguineti
Probabilistic lower bounds for approximation by shallow perceptron networks. Neural Networks 91 (2017)
Vera Kurková
Bounds on Sparsity of One-Hidden-Layer Perceptron Networks. ITAT (2017)
Vera Kurková
Multivariable Approximation by Convolutional Kernel Networks. ITAT (2016)
Vera Kurková, Marcello Sanguineti
Model complexities of shallow networks representing highly varying functions. Neurocomputing 171 (2016)
Vera Kurková
Lower Bounds on Complexity of Shallow Perceptron Networks. EANN (2016)
Vera Kurková
Complexity of Shallow Networks Representing Finite Mappings. ICAISC (1) (2015)
Vera Kurková
Limitations of One-Hidden-Layer Perceptron Networks. ITAT (2015)
Vera Kurková
Representations of Highly-Varying Functions by One-Hidden-Layer Networks. ICAISC (1) (2014)
Vera Kurková, Marcello Sanguineti
Complexity of Shallow Networks Representing Functions with Large Variations. ICANN (2014)
Vera Kurková, Paul C. Kainen
Comparing fixed and variable-width Gaussian networks. Neural Networks 57 (2014)
Vera Kurková, Marcello Sanguineti
Can Two Hidden Layers Make a Difference? ICANNGA (2013)
Vera Kurková
Surrogate solutions of Fredholm equations by feedforward networks. ITAT (2012)
Vera Kurková
Guest editorial: Adaptive and natural computing algorithms. Neurocomputing 96 (2012)
Vera Kurková
Surrogate Modelling of Solutions of Integral Equations by Neural Networks. AIAI (1) (2012)
Vera Kurková
Some Comparisons of Networks with Radial and Kernel Units. ICANN (2) (2012)
Paul C. Kainen, Vera Kurková, Marcello Sanguineti
Dependence of Computational Models on Input Dimension: Tractability of Approximation and Optimization Tasks. IEEE Trans. Inf. Theory 58 (2) (2012)
Giorgio Gnecco, Vera Kurková, Marcello Sanguineti
Accuracy of approximations of solutions to Fredholm equations by kernel methods. Appl. Math. Comput. 218 (14) (2012)
Vera Kurková
Complexity estimates based on integral transforms induced by computational units. Neural Networks 33 (2012)
Giorgio Gnecco, Vera Kurková, Marcello Sanguineti
Can dictionary-based computational models outperform the best linear ones? Neural Networks 24 (8) (2011)
Vera Kurková, Paul C. Kainen
Kernel Networks with Fixed and Variable Widths. ICANNGA (1) (2011)
Giorgio Gnecco, Vera Kurková, Marcello Sanguineti
Some comparisons of complexity in dictionary-based and linear computational models. Neural Networks 24 (2) (2011)
Giorgio Gnecco, Vera Kurková, Marcello Sanguineti
Bounds for Approximate Solutions of Fredholm Integral Equations Using Kernel Networks. ICANN (1) (2011)
Vera Kurková, Roman Neruda, Jan Koutník
Editorial. Neural Networks 23 (4) (2010)
Giorgio Gnecco, Vera Kurková, Marcello Sanguineti
Some Comparisons of Model Complexity in Linear and Neural-Network Approximation. ICANN (3) (2010)
Vera Kurková
Inverse Problems in Learning from Data. IJCCI (ICFC-ICNC) (2010)
Vera Kurková
Learning from Data as an Optimization and Inverse Problem. IJCCI (Selected Papers) (2010)
Paul C. Kainen, Vera Kurková
An Integral Upper Bound for Neural Network Approximation. Neural Comput. 21 (10) (2009)
Paul C. Kainen, Vera Kurková, Marcello Sanguineti
Complexity of Gaussian-radial-basis networks approximating smooth functions. J. Complex. 25 (1) (2009)
Vera Kurková
Model Complexity of Neural Networks and Integral Transforms. ICANN (1) (2009)
Paul C. Kainen, Vera Kurková, Marcello Sanguineti
On Tractability of Neural-Network Approximation. ICANNGA (2009)
Paul C. Kainen, Vera Kurková
Estimates of Network Complexity and Integral Representations. ICANN (1) (2008)
Vera Kurková
Minimization of Error Functionals over Perceptron Networks. Neural Comput. 20 (1) (2008)
Vera Kurková, Marcello Sanguineti
Geometric Upper Bounds on Rates of Variable-Basis Approximation. IEEE Trans. Inf. Theory 54 (12) (2008)
Vera Kurková, Marcello Sanguineti
Approximate Minimization of the Regularized Expected Error over Kernel Models. Math. Oper. Res. 33 (3) (2008)
Vera Kurková, Marcello Sanguineti
Geometric Rates of Approximation by Neural Networks. SOFSEM (2008)
Vera Kurková, Marcello Sanguineti
Estimates of covering numbers of convex sets with slowly decaying orthogonal subsets. Discret. Appl. Math. 155 (15) (2007)
Vera Kurková
Estimates of Data Complexity in Neural-Network Learning. SOFSEM (1) (2007)
Paul C. Kainen, Vera Kurková, Marcello Sanguineti
Estimates of Approximation Rates by Gaussian Radial-Basis Functions. ICANNGA (2) (2007)
Paul C. Kainen, Vera Kurková, Andrew Vogt
A Sobolev-type upper bound for rates of approximation by linear combinations of Heaviside plane waves. J. Approx. Theory 147 (1) (2007)
Vera Kurková
Neural Network Learning as an Inverse Problem. Log. J. IGPL 13 (5) (2005)
Vera Kurková, Marcello Sanguineti
Learning with generalization capability by kernel methods of bounded complexity. J. Complex. 21 (3) (2005)
Vera Kurková, Marcello Sanguineti
Error Estimates for Approximate Optimization by the Extended Ritz Method. SIAM J. Optim. 15 (2) (2005)
Paul C. Kainen, Vera Kurková, Marcello Sanguineti
Rates of Minimization of Error Functionals over Boolean Variable-Basis Functions. J. Math. Model. Algorithms 4 (4) (2005)
Paul C. Kainen, Vera Kurková, Marcello Sanguineti
Minimization of Error Functionals over Variable-Basis Functions. SIAM J. Optim. 14 (3) (2004)
Paul C. Kainen, Vera Kurková, Andrew Vogt
Best approximation by linear combinations of characteristic functions of half-spaces. J. Approx. Theory 122 (2) (2003)
Vera Kurková, Marcello Sanguineti
Neural network learning as approximate optimization. ICANNGA (2003)
Vera Kurková, Marcello Sanguineti
Comparison of worst case errors in linear and neural network approximation. IEEE Trans. Inf. Theory 48 (1) (2002)
Vera Kurková, Marcello Sanguineti
Bounds on rates of variable-basis and neural-network approximation. IEEE Trans. Inf. Theory 47 (6) (2001)
Paul C. Kainen, Vera Kurková, Andrew Vogt
Continuity of Approximation by Neural Networks in Lp Spaces. Ann. Oper. Res. 101 (1-4) (2001)
Vera Kurková, Marcello Sanguineti
Tight Bounds on Rates of Neural-Network Approximation. ICANN (2001)
Paul C. Kainen, Vera Kurková, Andrew Vogt
Best approximation by Heaviside perceptron networks. Neural Networks 13 (7) (2000)
Vera Kurková, Marcello Sanguineti
Comparison of Rates of Linear and Neural Network Approximation. IJCNN (1) (2000)
Paul C. Kainen, Vera Kurková, Andrew Vogt
Approximation by neural networks is not continuous. Neurocomputing 29 (1-3) (1999)
Vera Kurková
Approximation of Functions by Neural Networks. NC (1998)
Vera Kurková, Petr Savický, Katerina Hlavácková
Representations and rates of approximation of real-valued Boolean functions by neural networks. Neural Networks 11 (4) (1998)
Katerina Hlavácková, Vera Kurková, Petr Savický
Upper Bounds on the Approximation Rates of Real-valued Boolean Functions by Neural Networks. ICANNGA (1997)
Vera Kurková, Paul C. Kainen, Vladik Kreinovich
Estimates of the Number of Hidden Units and Variation with Respect to Half-Spaces. Neural Networks 10 (6) (1997)
Vera Kurková, Paul C. Kainen
A geometric method to obtain error-correcting classification by neural networks with fewer hidden units. ICNN (1996)
Katerina Hlavácková, Vera Kurková
Rates of approximation of real-valued boolean functions by neural networks. ESANN (1996)
Vera Kurková
Approximation of functions by perceptron networks with bounded number of hidden units. Neural Networks 8 (5) (1995)
Vera Kurková
Approximation of functions by Gaussian RBF networks with bouded number of hidden units. ESANN (1995)
Vera Kurková, Paul C. Kainen
Functionally Equivalent Feedforward Neural Networks. Neural Comput. 6 (3) (1994)
Vera Kurková, Katerina Hlavácková
Approximation of continuous functions by RBF and KBF networks. ESANN (1994)
Paul C. Kainen, Vera Kurková, Vladik Kreinovich, Ongard Sirisaengtaksin
Uniqueness of network parametrization and faster learning. Neural Parallel Sci. Comput. 2 (4) (1994)
Vera Kurková
Universal Approximation Using Feedforward Neural Networks with Gaussian Bar Units. ECAI (1992)
Vera Kurková
Kolmogorov's theorem and multilayer neural networks. Neural Networks 5 (3) (1992)
Vera Kurková
Kolmogorov's Theorem Is Relevant. Neural Comput. 3 (4) (1991)