Cesko.wiki Věra Kůrková
Author
Albert FloresVěra Kůrková (* 1948) je česká matematička zabývající se především teorií nelineární aproximace a optimalizace, matematickou teorií neuronových sítí a teorií učení.
V roce 1972 absolvovala Matematicko-fyzikální fakultu Univerzity Karlovy, obor topologie. Je členkou vědecké rady Ústavu informatiky AV ČR, kde pracuje od roku 1990. +more Od roku 2001 je též členkou Oborové rady 1: Matematické a fyzikální vědy a informatika Grantové agentury AV.
Dílo
Seznam děl:
* V. Kůrková, M. +more Sanguineti: Model complexities of shallow networks representing highly varying functions, Neurocomputing 171, 598-604, 2016. * V. Kůrková, P. C. Kainen: Comparing fixed and variable-width Gaussian networks, Neural Networks (57): 23-28, 2014. * V. Kůrková: Complexity estimates based on integral transforms induced by computational units, Neural Networks (33): 160-167, 2012. * G. Gnecco, V. Kůrková: Sanguineti: Accuracy of approximations of solutions to Fredholm equations by kernel methods. Applied Mathematics and Computation, 218(14), 7481-7497, 2012. * P. C. Kainen, V. Kůrková, M. Sanguineti: Dependence of Computational Models on Input Dimension: Tractability of Approximation and Optimization Tasks. IEEE Transactions on Information Theory 58(2): 1203-1214, 2012. * G. Gnecco, V. Kůrková, M. Sanguineti: Can dictionary-based computational models outperform the best linear ones. Neural Networks 24(8): 881-887, 2011. * G. Gnecco, V. Kůrková, M. Sanguineti: Some comparisons of complexity in dictionary-based and linear computational models. Neural Networks 24(1): 171-182, 2011. * P. C. Kainen, V. Kůrková, A. Vogt: Integral combinations of Heavisides. Math. Nachr. 283(6): 854-878, 2010. * P. C. Kainen, V. Kůrková: An Integral Upper Bound for Neural Network Approximation. Neural Computation 21(2009): 2970-2989, 2009. * P. C. Kainen, V. Kůrková, M. Sanguineti: Complexity of Gaussian radial basis networks approximating smooth functions. Journal of Complexity 25(2009): 63-74, 2009. * V. Kůrková, M. Sanguineti: Geometric Upper Bounds on Rates of Variable-Basis Approximation. IEEE Transactions on Information Theory, 54(12): 5681-5688, 2008. * V. Kůrková, M. Sanguineti: Approximate minimization of the regularized expected error over kernel models. Mathematics of Operations Research 33(3): 747-756, 2008. * V. Kůrková: Minimization of error functionals over perceptron networks. Neural Computation 20(1): 252-270, 2008. * V. Kůrková, M. Sanguineti: Estimates of covering numbers of convex sets with slowly decaying orthogonal subsets. Discrete Applied Mathematics 155: 1930-1942, 2007. * P. C. Kainen, V. Kůrková, A. Vogt: A Sobolev-type upper bound for rates of approximation by linear combinations of Heaviside plane waves. Journal of Approximation Theory 147: 1-10, 2007. * V. Kůrková: Supervised learning with generalization as an inverse problem. Logic Journal of IGPL 13: 551-559, 2005. * V. Kůrková, M. Sanguineti: Learning with generalization capability by kernel methods of bounded complexity. Journal of Complexity 21: 350-367, 2005. * V. Kurková, M. Sanguineti: Error estimates for approximate optimization by the extended Ritz method. SIAM Journal on Optimization, 15, 2, 2005, pp. 461-487. * P. C. Kainen, V. Kůrková, M. Sanguineti: Rates of approximate minimization of error functionals over Boolean variable-basis functions. Journal of Mathematical Modelling and Algorithms 4: 355-368, 2005. * P. C. Kainen, V. Kůrková, M. Sanguineti: Minimization of error functionals over neural networks. SIAM Journal on Optimization 14: 732-742, 2003. * P. C. Kainen, V. Kůrková, A. Vogt: Best approximation by linear combinations of characteristic functions of half-spaces. Journal of Approximation Theory 151-159, 2003. * V. Kůrková, M. Sanguineti: Comparison of worst-case errors in linear and neural network approximation.