Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Vladimir Kryzhanovskiy"'
Publikováno v:
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6c8e01c65002ac16bb43caaecf09459a
https://doi.org/10.1109/cvpr52688.2022.01218
https://doi.org/10.1109/cvpr52688.2022.01218
Publikováno v:
CVPR
Modern deep neural networks (DNNs) cannot be effectively used in mobile and embedded devices due to strict requirements for computational complexity, memory, and power consumption. The quantization of weights and feature maps (activations) is a popul
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c74d5a5fbe85d7a03504f6bd7ec67278
https://doi.org/10.1109/cvpr46437.2021.01054
https://doi.org/10.1109/cvpr46437.2021.01054
Autor:
Vitalii Bushaev, Mikhail A. Kudinov, Vladimir Kryzhanovskiy, Vadim Popov, Tasnima Sadekova, Stanislav Kamenev, Sergey Repyevsky, Denis Parkhomenko
Publikováno v:
INTERSPEECH
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ffe2c1a06adce0bd52c7abe36074614e
https://doi.org/10.21437/interspeech.2020-2169
https://doi.org/10.21437/interspeech.2020-2169
Publikováno v:
Springer Series in Bio-/Neuroinformatics ISBN: 9783319099026
A new model – Double-Layer Vector Perceptron (DLVP) – is proposed. Compared with a single-layer perceptron, its operation requires slightly more computations (by 5%) and more effective computer memory, but it excels at a much lower error rate (fo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4aa1ff93e83eb1c74e6b8ef66ab053f9
https://doi.org/10.1007/978-3-319-09903-3_5
https://doi.org/10.1007/978-3-319-09903-3_5
Publikováno v:
Artificial Intelligence and Soft Computing ISBN: 9783642293467
ICAISC (1)
ICAISC (1)
A number of researchers headed by E. Gardner have proved that a maximum achievable memory load of binary perceptron is 2. A learning algorithm allowing reaching and even exceeding the critical load was proposed. The algorithm was reduced to solving t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::884dbf43205302c21374d78cbb1cca5e
https://doi.org/10.1007/978-3-642-29347-4_13
https://doi.org/10.1007/978-3-642-29347-4_13
Publikováno v:
Artificial Neural Networks and Machine Learning – ICANN 2012 ISBN: 9783642332654
ICANN (2)
ICANN (2)
Application of Linear Programming for binary perceptron learning allows reaching theoretical maximum loading of the perceptron that had been predicted by E. Gardner. In the present paper the idea of learning using Linear Programming is extended to ve
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0df4faafa887ed754e2e9e834066c020
https://doi.org/10.1007/978-3-642-33266-1_25
https://doi.org/10.1007/978-3-642-33266-1_25
Autor:
Vladimir Kryzhanovskiy
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783642217371
ICANN (2)
ICANN (2)
I describe a new vector neural network, in which a priori information about the distribution of noise is easily and naturally embedded. Taking into account the noise distribution allows to essentially increase the system noise immunity. A measure of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0fa530e71b51fd1207e297304f581dd2
https://doi.org/10.1007/978-3-642-21738-8_16
https://doi.org/10.1007/978-3-642-21738-8_16