Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Petra Vidnerová"'
Autor:
Roman Neruda, Petra Vidnerová
Publikováno v:
Neural networks : the official journal of the International Neural Network Society. 127
This paper deals with the vulnerability of machine learning models to adversarial examples and its implication for robustness and generalization properties. We propose an evolutionary algorithm that can generate adversarial examples for any machine l
Autor:
Roman Neruda, Petra Vidnerová
Publikováno v:
Artifical Intelligence and Soft Computing ISBN: 9783642132315
ICAISC (2)
ICAISC (2)
Regularization theory presents a sound framework to solving supervised learning problems. However, the regularization networks have a large size corresponding to the size of training data. In this work we study a relationship between network complexi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2a60a8443a9d11b5a0b276107a642fa5
https://doi.org/10.1007/978-3-642-13232-2_15
https://doi.org/10.1007/978-3-642-13232-2_15
Autor:
Roman Neruda, Petra Vidnerová
Publikováno v:
Advances in Information Technology ISBN: 9783642166983
IAIT
IAIT
Regularization networks are one of the important methods for supervised learning. They benefit from very good theoretical background, though their drawback is the presence of metaparameters. The metaparameters are typically supposed to be given by an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::be9ed1bc4828e1abd07fe7b001d3ebae
https://doi.org/10.1007/978-3-642-16699-0_21
https://doi.org/10.1007/978-3-642-16699-0_21
Autor:
Roman Neruda, Petra Vidnerová
Publikováno v:
2008 Second International Conference on Future Generation Communication and Networking Symposia.
There is a gap between the theoretical results of regularization theory and practical suitability of regularization-derived networks (RN). On the other hand, radial basis function networks (RBF) that can be seen as a special case of regularization ne
Autor:
Petra Vidnerová, Roman Neruda
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783540877318
ISNN (1)
ISNN (1)
Regularization theory presents a sound framework to solving supervised learning problems. However, there is a gap between the theoretical results and practical suitability of regularization networks (RN). Radial basis function networks (RBF) can be s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c631ab6c015615bf4645658756a00a53
https://doi.org/10.1007/978-3-540-87732-5_61
https://doi.org/10.1007/978-3-540-87732-5_61