Kůrková Věra

Publikace ASEP

Další varianty jména: Pohlová, Věra; Kůrková-Pohlová, Věra
RIV ID 9769439               

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Nalezeno záznamů: 17

0398349 - UIVT-O 2014 RIV DE eng M - Část monografie knihy
Kůrková, Věra
Accuracy of surrogate solutions of integral equations by feedforward networks.
Issues and Challenges of Intelligent Systems and Computational Intelligence. Cham: Springer, 2014 - (Kóczy, L.; Pozna, C.; Kacprzyk, J.), s. 91-102. Studies in Computational Intelligence, 530. ISBN 978-3-319-03205-4
Grant CEP: GA ČR GAP202/11/1368; GA MŠk(CZ) LD13002
Institucionální podpora: RVO:67985807
Klíčová slova: surrogate modeling by neural networks * approximate solutions of integral equations * feedforward neural networks * model complexity * rates of approximation
Kód oboru RIV: IN - Informatika
Trvalý odkaz: http://hdl.handle.net/11104/0225861

0478625 - UIVT-O 2018 RIV DE eng C - Konferenční příspěvek (zahraniční konf.)
Kůrková, Věra
Bounds on Sparsity of One-Hidden-Layer Perceptron Networks.
Proceedings ITAT 2017: Information Technologies - Applications and Theory. Aachen & Charleston: Technical University & CreateSpace Independent Publishing Platform, 2017 - (Hlaváčová, J.), s. 100-105. CEUR Workshop Proceedings, V-1885. ISBN 978-1974274741. ISSN 1613-0073.
[ITAT 2017. Conference on Theory and Practice of Information Technologies - Applications and Theory /17./. Martinské hole (SK), 22.09.2017-26.09.2017]
Grant CEP: GA ČR GA15-18108S
Institucionální podpora: RVO:67985807
Klíčová slova: shallow perceptron networks * sparse networks * pseudo-noise sequences * variational norm
Kód oboru RIV: IN - Informatika
Obor OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
http://ceur-ws.org/Vol-1885/100.pdf
Trvalý odkaz: http://hdl.handle.net/11104/0274766

0428366 - UIVT-O 2015 RIV GB eng J - Článek v odborném periodiku
Kůrková, Věra - Kainen, P.C.
Comparing Fixed and Variable-Width Gaussian Networks.
Neural Networks. Roč. 57, September (2014), s. 23-28. ISSN 0893-6080
Grant CEP: GA MŠk(CZ) LD13002
Institucionální podpora: RVO:67985807
Klíčová slova: Gaussian radial and kernel networks * Functionally equivalent networks * Universal approximators * Stabilizers defined by Gaussian kernels * Argminima of error functionals
Kód oboru RIV: IN - Informatika
Impakt faktor: 2.708, rok: 2014
Kůrková, Věra
Trvalý odkaz: http://hdl.handle.net/11104/0233708

Citace, recenze

Citace:
COUFAL, D. Radial fuzzy systems. FUZZY SETS AND SYSTEMS. ISSN 0165-0114, JUL 15 2017, vol. 319, p. 1-27.
YE, F. - WANG, H. - LI, G.Y. Variable stiffness composite material design by using support vector regression assisted efficient global optimization method. STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION. ISSN 1615-147X, JUL 2017, vol. 56, no. 1, p. 203-219.
VIDNEROVA, P. - NERUDA, R. Sensor Data Air Pollution Prediction by Kernel Models. 2016 16TH IEEE/ACM INTERNATIONAL SYMPOSIUM ON CLUSTER, CLOUD AND GRID COMPUTING (CCGRID). ISSN 2376-4414, 2016, p. 666-673.
VIDNEROVA, P. - NERUDA, R. Product Multi-kernels for Sensor Data Analysis. ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING, PT I. ISSN 0302-9743, 2015, vol. 9119, p. 123-133.

0443724 - UIVT-O 2016 RIV CH eng C - Konferenční příspěvek (zahraniční konf.)
Kůrková, Věra
Complexity of Shallow Networks Representing Finite Mappings.
Artificial Intelligence and Soft Computing. Vol. 1. Cham: Springer, 2015 - (Rutkowski, L.; Korytkowski, M.; Scherer, R.; Tadeusiewicz, R.; Zadeh, L.; Zurada, J.), s. 39-48. Lecture Notes in Artificial Intelligence, 9119. ISBN 978-3-319-19323-6. ISSN 0302-9743.
[ICAISC 2015. International Conference on Artificial Intelligence and Soft Computing /14./. Zakopane (PL), 12.06.2015-16.06.2015]
Grant CEP: GA ČR GA15-18108S
Institucionální podpora: RVO:67985807
Klíčová slova: Shallow feedforward networks * Signum perceptrons * Finite mappings * Model complexity * Hadamard matrices
Kód oboru RIV: IN - Informatika
Trvalý odkaz: http://hdl.handle.net/11104/0246406

Citace, recenze

Citace:
VASILYEV, V. Structural Design Of Shallow Neural Networks On The Basis Of Minimal Complexity Principle. 2016 24TH MEDITERRANEAN CONFERENCE ON CONTROL AND AUTOMATION (MED). ISSN 2325-369X, 2016, p. 1212-1217.

0430374 - UIVT-O 2015 RIV CH eng C - Konferenční příspěvek (zahraniční konf.)
Kůrková, Věra - Sanguineti, M.
Complexity of Shallow Networks Representing Functions with Large Variations.
Artificial Neural Networks and Machine Learning - ICANN 2014. Cham: Springer, 2014 - (Wermter, S.; Weber, C.; Duch, W.; Honkela, T.; Koprinkova-Hristova, P.; Magg, S.; Palm, G.; Villa, A.), s. 331-338. Lecture Notes in Computer Science, 8681. ISBN 978-3-319-11178-0.
[ICANN 2014. International Conference on Artificial Neural Networks /24./. Hamburg (DE), 15.09.2014-19.09.2014]
Grant CEP: GA MŠk(CZ) LD13002
Institucionální podpora: RVO:67985807
Klíčová slova: one-hidden-layer networks * model complexity * representations of multivariable functions * perceptrons * Gaussian SVMs
Kód oboru RIV: IN - Informatika
Trvalý odkaz: http://hdl.handle.net/11104/0235318

0474092 - UIVT-O 2019 RIV US eng J - Článek v odborném periodiku
Kůrková, Věra
Constructive Lower Bounds on Model Complexity of Shallow Perceptron Networks.
Neural Computing & Applications. Roč. 29, č. 7 (2018), s. 305-315. ISSN 0941-0643
Grant CEP: GA ČR GA15-18108S
Institucionální podpora: RVO:67985807
Klíčová slova: shallow and deep networks * model complexity and sparsity * signum perceptron networks * finite mappings * variational norms * Hadamard matrices
Kód oboru RIV: IN - Informatika
Obor OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Impakt faktor: 4.664, rok: 2018
Trvalý odkaz: http://hdl.handle.net/11104/0271209

0447921 - UIVT-O 2016 RIV DE eng C - Konferenční příspěvek (zahraniční konf.)
Kůrková, Věra
Limitations of One-Hidden-Layer Perceptron Networks.
Proceedings ITAT 2015: Information Technologies - Applications and Theory. Aachen & Charleston: Technical University & CreateSpace Independent Publishing Platform, 2015 - (Yaghob, J.), s. 167-171. CEUR Workshop Proceedings, V-1422. ISBN 978-1-5151-2065-0. ISSN 1613-0073.
[ITAT 2015. Conference on Theory and Practice of Information Technologies /15./. Slovenský Raj (SK), 17.09.2015-21.09.2015]
Grant CEP: GA MŠk(CZ) LD13002
Institucionální podpora: RVO:67985807
Klíčová slova: perceptron networks * model complexity * representations of finite mappings by neural networks
Kód oboru RIV: IN - Informatika
Trvalý odkaz: http://hdl.handle.net/11104/0249675

Citace, recenze

Citace:
VASILYEV, V. Structural Design Of Shallow Neural Networks On The Basis Of Minimal Complexity Principle. 2016 24TH MEDITERRANEAN CONFERENCE ON CONTROL AND AUTOMATION (MED). ISSN 2325-369X, 2016, p. 1212-1217.

0460704 - UIVT-O 2017 RIV CH eng C - Konferenční příspěvek (zahraniční konf.)
Kůrková, Věra
Lower Bounds on Complexity of Shallow Perceptron Networks.
Engineering Applications of Neural Networks. Cham: Springer, 2016 - (Jayne, C.; Iliadis, L.), s. 283-294. Communications in Computer and Information Science, 629. ISBN 978-3-319-44187-0. ISSN 1865-0929.
[EANN 2016. International Conference /17./. Aberdeen (GB), 02.09.2016-05.09.2016]
Grant CEP: GA ČR GA15-18108S
Institucionální podpora: RVO:67985807
Klíčová slova: shallow feedforward networks * signum perceptrons * finite mappings * model complexity * Hadamard matrices
Kód oboru RIV: IN - Informatika
Obor OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Trvalý odkaz: http://hdl.handle.net/11104/0260719

Citace, recenze

Citace:
COSTARELLI, D. - VINTI, G. Saturation Classes for Max-Product Neural Network Operators Activated by Sigmoidal Functions. RESULTS IN MATHEMATICS. ISSN 1422-6383, NOV 2017, vol. 72, no. 3, p. 1555-1569.
COSTARELLI, D. - VINTI, G. Estimates for the Neural Network Operators of the Max-Product Type with Continuous and p-Integrable Functions. RESULTS IN MATHEMATICS. ISSN 1422-6383, MAR 2018, vol. 73, no. 1.
GULIYEV, N.J. - ISMAILOV, V.E. On the approximation by single hidden layer feedforward neural networks with fixed weights. NEURAL NETWORKS. ISSN 0893-6080, FEB 2018, vol. 98, p. 296-304.

0446410 - UIVT-O 2016 RIV NL eng J - Článek v odborném periodiku
Kůrková, Věra - Sanguineti, M.
Model Complexities of Shallow Networks Representing Highly Varying Functions.
Neurocomputing. Roč. 171, 1 January (2016), s. 598-604. ISSN 0925-2312
Grant CEP: GA MŠk(CZ) LD13002
grant for Visiting Professors(IT) GNAMPA-INdAM
Institucionální podpora: RVO:67985807
Klíčová slova: shallow networks * model complexity * highly varying functions * Chernoff bound * perceptrons * Gaussian kernel units
Kód oboru RIV: IN - Informatika
Impakt faktor: 3.317, rok: 2016
Trvalý odkaz: http://hdl.handle.net/11104/0248405

Citace, recenze

Citace:
BIANCHINI, M. - BELAHCEN, A. - SCARSELLI, F. A Comparative Study of Inductive and Transductive Learning with Feedforward Neural Networks. AI*IA 2016: ADVANCES IN ARTIFICIAL INTELLIGENCE. ISSN 0302-9743, 2016, vol. 10037, p. 283-293.
COSTARELLI, D. - VINTI, G. Approximation theorems for a family of multivariate neural network operators in Orlicz-type spaces. RICERCHE DI MATEMATICA. ISSN 0035-5038, NOV 2018, vol. 67, no. 2, p. 387-399.
VASILYEV, V.I. - LOZHNIKOV, P.S. - SULAVKO, A.E. - FOFANOV, G.A. - ZHUMAZHANOVA, S.S.S. Flexible fast learning neural networks and their application for building highly reliable biometric cryptosystems based on dynamic features. IFAC PAPERSONLINE. ISSN 2405-8963, 2018, vol. 51, no. 30, p. 527-532.
COSTARELLI, D. - VINTI, G. CONVERGENCE RESULTS FOR A FAMILY OF KANTOROVICH MAX-PRODUCT NEURAL NETWORK OPERATORS IN A MULTIVARIATE SETTING. MATHEMATICA SLOVACA. ISSN 0139-9918, NOV 2017, vol. 67, no. 6, p. 1469-1480.

0449922 - UIVT-O 2016 RIV SK cze C - Konferenční příspěvek (zahraniční konf.)
Kůrková, Věra
Modelová složitost neuronových sítí - zdánlivý paradox.
[Model Complexity of Neural Networks - a Seeming Paradox.]
Kognícia a umelý život 2015. Bratislava: Univerzita Komenského v Bratislave, 2015 - (Farkaš, I.; Takáč, M.; Rybár, J.; Kelemen, J.), s. 102-106. ISBN 978-80-223-3875-2.
[Kognícia a umelý život /15./. Trenčianske Teplice (SK), 25.05.2015-28.05.2015]
Grant CEP: GA MŠk(CZ) LD13002
Institucionální podpora: RVO:67985807
Klíčová slova: model complexity of feedforward neural networks * one-hidden-layer networks * concentration of measure
Kód oboru RIV: IN - Informatika
http://cogsci.fmph.uniba.sk/kuz2015/zbornik/prispevky/kurkova.pdf
Trvalý odkaz: http://hdl.handle.net/11104/0251322

0462912 - UIVT-O 2017 RIV DE eng C - Konferenční příspěvek (zahraniční konf.)
Kůrková, Věra
Multivariable Approximation by Convolutional Kernel Networks.
Proceedings ITAT 2016: Information Technologies - Applications and Theory. Aachen & Charleston: Technical University & CreateSpace Independent Publishing Platform, 2016 - (Brejová, B.), s. 118-122. CEUR Workshop Proceedings, V-1649. ISBN 978-1-5370-1674-0. ISSN 1613-0073.
[ITAT 2016. Conference on Theory and Practice of Information Technologies /16./. Tatranské Matliare (SK), 15.09.2016-19.09.2016]
Grant CEP: GA ČR GA15-18108S
Institucionální podpora: RVO:67985807
Klíčová slova: kernel networks * approximation of functions * Fourier transform
Kód oboru RIV: IN - Informatika
Obor OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
http://ceur-ws.org/Vol-1649/118.pdf
Trvalý odkaz: http://hdl.handle.net/11104/0262258

0493926 - UIVT-O 2019 RIV DE eng C - Konferenční příspěvek (zahraniční konf.)
Kůrková, Věra - Sanguineti, M.
Probabilistic Bounds on Complexity of Networks Computing Binary Classification Tasks.
ITAT 2018: Information Technologies – Applications and Theory. Proceedings of the 18th conference ITAT 2018. Aachen: Technical University & CreateSpace Independent Publishing Platform, 2018 - (Krajči, S.), s. 86-91. CEUR Workshop Proceedings, V-2203. ISSN 1613-0073.
[ITAT 2018. Conference on Information Technologies – Applications and Theory /18./. Plejsy (SK), 21.09.2018-25.09.2018]
Grant CEP: GA ČR(CZ) GA18-23827S
Institucionální podpora: RVO:67985807
Klíčová slova: feedforward networks * binary classification * measures of sparsity * probabilistic bounds * dictionaries of computational units
Kód oboru RIV: IN - Informatika
Obor OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
http://ceur-ws.org/Vol-2203/86.pdf
Trvalý odkaz: http://hdl.handle.net/11104/0287193

0473964 - UIVT-O 2018 RIV GB eng J - Článek v odborném periodiku
Kůrková, Věra - Sanguineti, M.
Probabilistic Lower Bounds for Approximation by Shallow Perceptron Networks.
Neural Networks. Roč. 91, July (2017), s. 34-41. ISSN 0893-6080
Grant CEP: GA ČR GA15-18108S
Institucionální podpora: RVO:67985807
Klíčová slova: shallow networks * perceptrons * model complexity * lower bounds on approximation rates * Chernoff-Hoeffding bounds
Kód oboru RIV: IN - Informatika
Obor OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Impakt faktor: 7.197, rok: 2017
Trvalý odkaz: http://hdl.handle.net/11104/0271067

Citace, recenze

Citace:
LOPEZ-MARTIN, M. - CARRO, B. - SANCHEZ-ESGUEVILLAS, A. - LLORET, J. Shallow neural network with kernel approximation for prediction problems in highly demanding data networks. EXPERT SYSTEMS WITH APPLICATIONS. ISSN 0957-4174, JUN 15 2019, vol. 124, p. 196-208.
GORBAN, A.N. - GOLUBKOV, A. - GRECHUK, B. - MIRKES, E.M. - TYUKIN, I.Y. Correction of AI systems by linear discriminants: Probabilistic foundations. INFORMATION SCIENCES. ISSN 0020-0255, OCT 2018, vol. 466, p. 303-322.
GORBAN, A.N. - TYUKIN, I.Y. Blessing of dimensionality: mathematical foundations of the statistical physics of data. PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES. ISSN 1364-503X, APR 28 2018, vol. 376, no. 2118.
VASILYEV, V.I. - LOZHNIKOV, P.S. - SULAVKO, A.E. - FOFANOV, G.A. - ZHUMAZHANOVA, S.S.S. Flexible fast learning neural networks and their application for building highly reliable biometric cryptosystems based on dynamic features. IFAC PAPERSONLINE. ISSN 2405-8963, 2018, vol. 51, no. 30, p. 527-532.

0432428 - UIVT-O 2015 RIV CZ eng C - Konferenční příspěvek (zahraniční konf.)
Kůrková, Věra
Representations of Boolean Functions by Perceptron Networks.
ITAT 2014. Information Technologies - Applications and Theory. Part II. Prague: Institute of Computer Science AS CR, 2014 - (Kůrková, V.; Bajer, L.; Peška, L.; Vojtáš, R.; Holeňa, M.; Nehéz, M.), s. 68-70. ISBN 978-80-87136-19-5.
[ITAT 2014. European Conference on Information Technologies - Applications and Theory /14./. Demänovská dolina (SK), 25.09.2014-29.09.2014]
Grant CEP: GA MŠk(CZ) LD13002
Institucionální podpora: RVO:67985807
Klíčová slova: perceptron networks * model complexity * Boolean functions
Kód oboru RIV: IN - Informatika
Trvalý odkaz: http://hdl.handle.net/11104/0236782

0427584 - UIVT-O 2015 RIV CH eng C - Konferenční příspěvek (zahraniční konf.)
Kůrková, Věra
Representations of Highly-Varying Functions by One-Hidden-Layer Networks.
Artificial Intelligence and Soft Computing Part I. Cham: Springer, 2014 - (Rutkowski, L.; Korytkowski, M.; Scherer, R.; Tadeusiewicz, R.; Zadeh, L.; Zurada, J.), s. 67-76. Lecture Notes in Artificial Intelligence, 8467. ISBN 978-3-319-07172-5. ISSN 0302-9743.
[ICAISC 2014. International Conference on Artificial Intelligence and Soft Computing /13./. Zakopane (PL), 01.06.2014-05.06.2014]
Grant CEP: GA MŠk(CZ) LD13002
Institucionální podpora: RVO:67985807
Klíčová slova: model complexity of neural networks * one-hidden-layer networks * highly-varying functions * tractability of representations of multivariable functions by neural networks
Kód oboru RIV: IN - Informatika
Trvalý odkaz: http://hdl.handle.net/11104/0233103

0493825 - UIVT-O 2019 RIV CH eng C - Konferenční příspěvek (zahraniční konf.)
Kůrková, Věra
Sparsity and Complexity of Networks Computing Highly-Varying Functions.
Artificial Neural Networks and Machine Learning – ICANN 2018. Proceedings, Part III. Cham: Springer, 2018 - (Kůrková, V.; Manolopoulos, Y.; Hammer, B.; Iliadis, L.; Maglogiannis, I.), s. 534-543. Lecture Notes in Computer Science, 11141. ISBN 978-3-030-01423-0. ISSN 0302-9743.
[ICANN 2018. International Conference on Artificial Neural Networks /27./. Rhodes (GR), 04.10.2018-07.10.2018]
Grant CEP: GA ČR(CZ) GA18-23827S
Institucionální podpora: RVO:67985807
Klíčová slova: Shallow and deep networks * Model complexity * Sparsity * Highly-varying functions * Covering numbers * Dictionaries of computational units * Perceptrons
Kód oboru RIV: IN - Informatika
Obor OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
https://www.springer.com/us/book/9783030014230
Kůrková, Věra
Trvalý odkaz: http://hdl.handle.net/11104/0287121

0476509 - UIVT-O 2018 RIV CH eng C - Konferenční příspěvek (zahraniční konf.)
Kůrková, Věra
Sparsity of Shallow Networks Representing Finite Mappings.
EANN 2017. Cham: Springer, 2017 - (Boracchi, G.; Iliadis, L.; Jayne, C.; Likas, A.), s. 337-348. Communications in Computer and Information Science, 744. ISBN 978-3-319-65171-2. ISSN 1865-0929.
[EANN 2017. International Conference /18./. Athens (GR), 25.08.2017-27.08.2017]
Grant CEP: GA ČR GA15-18108S
Institucionální podpora: RVO:67985807
Klíčová slova: shallow networks * finite mappings * sparsity * model complexity * concentration of measure * signum perceptrons
Kód oboru RIV: IN - Informatika
Obor OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Trvalý odkaz: http://hdl.handle.net/11104/0272989