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0474092 - ÚI 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. E-ISSN 1433-3058
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
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 link: http://hdl.handle.net/11104/0271209
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. E-ISSN 1433-3058
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
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 link: http://hdl.handle.net/11104/0271209