Zobrazeno 1 - 10
of 59
pro vyhledávání: '"Evgeny M. Mirkes"'
Autor:
Innokentiy A. Kastalskiy, Evgeniya V. Pankratova, Evgeny M. Mirkes, Victor B. Kazantsev, Alexander N. Gorban
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
Abstract The dynamics of epidemics depend on how people's behavior changes during an outbreak. At the beginning of the epidemic, people do not know about the virus, then, after the outbreak of epidemics and alarm, they begin to comply with the restri
Externí odkaz:
https://doaj.org/article/7a2816dc1dcd4a1fa4b93e287f83ddac
Autor:
Evgeny M. Mirkes, Jonathan Bac, Aziz Fouché, Sergey V. Stasenko, Andrei Zinovyev, Alexander N. Gorban
Publikováno v:
Entropy, Vol 25, Iss 1, p 33 (2022)
Domain adaptation is a popular paradigm in modern machine learning which aims at tackling the problem of divergence (or shift) between the labeled training and validation datasets (source domain) and a potentially large unlabeled dataset (target doma
Externí odkaz:
https://doaj.org/article/fc1cb24a684747288609251ceb7b827a
Publikováno v:
Sensors, Vol 21, Iss 22, p 7662 (2021)
Data on artificial night-time light (NTL), emitted from the areas, and captured by satellites, are available at a global scale in panchromatic format. In the meantime, data on spectral properties of NTL give more information for further analysis. Suc
Externí odkaz:
https://doaj.org/article/9f9ab06a3a7243b5a724791a8e787ab2
Publikováno v:
Entropy, Vol 23, Iss 10, p 1368 (2021)
Dealing with uncertainty in applications of machine learning to real-life data critically depends on the knowledge of intrinsic dimensionality (ID). A number of methods have been suggested for the purpose of estimating ID, but no standard package to
Externí odkaz:
https://doaj.org/article/bb953d6fe9de408f92149c8b374d76c1
Autor:
Santos J. Núñez Jareño, Daniël P. van Helden, Evgeny M. Mirkes, Ivan Y. Tyukin, Penelope M. Allison
Publikováno v:
Entropy, Vol 23, Iss 9, p 1140 (2021)
In this article, we consider a version of the challenging problem of learning from datasets whose size is too limited to allow generalisation beyond the training set. To address the challenge, we propose to use a transfer learning approach whereby th
Externí odkaz:
https://doaj.org/article/41f7b167a5eb45f8bcec221b1bf487b3
Publikováno v:
Entropy, Vol 23, Iss 8, p 1090 (2021)
This work is driven by a practical question: corrections of Artificial Intelligence (AI) errors. These corrections should be quick and non-iterative. To solve this problem without modification of a legacy AI system, we propose special ‘external’
Externí odkaz:
https://doaj.org/article/f08d1a0e0db047fdbcc49f1cee97f830
Publikováno v:
Entropy, Vol 22, Iss 10, p 1105 (2020)
The curse of dimensionality causes the well-known and widely discussed problems for machine learning methods. There is a hypothesis that using the Manhattan distance and even fractional lp quasinorms (for p less than 1) can help to overcome the curse
Externí odkaz:
https://doaj.org/article/4ab622c5196541fea3e463d29b049b7a
Autor:
Evgeny M. Mirkes
Publikováno v:
Entropy, Vol 22, Iss 3, p 264 (2020)
Recently, A.N. Gorban presented a rich family of universal Lyapunov functions for any linear or non-linear reaction network with detailed or complex balance. Two main elements of the construction algorithm are partial equilibria of reactions and conv
Externí odkaz:
https://doaj.org/article/34694466a43946abba797a75ea5da239
Autor:
Petra Jones, Evgeny M. Mirkes, Tom Yates, Charlotte L. Edwardson, Mike Catt, Melanie J. Davies, Kamlesh Khunti, Alex V. Rowlands
Publikováno v:
Sensors, Vol 19, Iss 20, p 4504 (2019)
Few methods for classifying physical activity from accelerometer data have been tested using an independent dataset for cross-validation, and even fewer using multiple independent datasets. The aim of this study was to evaluate whether unsupervised m
Externí odkaz:
https://doaj.org/article/15b64670b4b84bf3a054933b6f039e1b
Autor:
Evgeny M. Mirkes, Alexander N. Gorban, Victor B. Kazantsev, Evgeniya V. Pankratova, Innokentiy Kastalskiy
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
Scientific Reports
Scientific Reports
The dynamics of epidemics depend on how people's behavior changes during an outbreak. At the beginning of the epidemic, people do not know about the virus, then, after the outbreak of epidemics and alarm, they begin to comply with the restrictions an