Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Ilona M. Kulikovskikh"'
Autor:
Tarzan Legović, Ilona M. Kulikovskikh
Publikováno v:
GECCO Companion
Training neural networks with faster gradient methods brings them to the edge of stability, proximity to which improves their generalization capability. However, it is not clear how to stably approach the edge. We propose a new activation function to
Publikováno v:
Entropy (Basel. Online)
Entropy
Volume 22
Issue 8
Entropy, Vol 22, Iss 906, p 906 (2020)
Entropy
Volume 22
Issue 8
Entropy, Vol 22, Iss 906, p 906 (2020)
Machines usually employ a guess-and-check strategy to analyze data: they take the data, make a guess, check the answer, adjust it with regard to the correct one if necessary, and try again on a new data set. An active learning environment guarantees
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dec77b1324d9009b94731094199203c5
https://doi.org/10.3390/e22080906
https://doi.org/10.3390/e22080906
Autor:
Ilona M. Kulikovskikh
Publikováno v:
Automation and Remote Control. 79:1458-1473
Consideration was given to a new representation of the Meixner filters which, in distinction to the previously proposed filters, have a rational form of representation of any integer values of the additional parameter α, can be used to describe the
Autor:
Ilona M. Kulikovskikh
Publikováno v:
Engineering Applications of Artificial Intelligence. 65:330-335
Most environmental parameters are clearly indicative of occupants’ presence and subtle changes in their behavior. However, this variation in sensor data makes it challenging to create a proper measure of occupancy detection that is both robust and
Publikováno v:
Computers in Human Behavior. 75:81-91
Collaborative learning is a promising avenue in education research. Learning from others and with others can foster deeper learning at a multiple-choice assignment, but it is hard to control the level of students' pure guessing. This paper addresses
Autor:
S.A. Prokhorov, Ilona M. Kulikovskikh
Publikováno v:
Procedia Engineering. 201:779-788
The problem of complete separation between classes may produce serious difficulties with the successful implementation of logistic regression due to the presence of floor and ceiling effects. To address this problem, the present study proposes two mo
Autor:
Ilona M. Kulikovskikh, S.A. Prokhorov
Publikováno v:
Международный журнал "Программные продукты и системы". 36:99-101
Publikováno v:
PLoS ONE
PLoS ONE, Vol 14, Iss 7, p e0219004 (2019)
PLoS ONE, Vol 14, Iss 7, p e0219004 (2019)
Recent research in machine learning pointed to the core problem of state-of-the-art models which impedes their widespread adoption in different domains. The models' inability to differentiate between noise and subtle, yet significant variation in dat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::38bf1c8959aea2d7d2f6d59a4557aef6
https://doi.org/10.1371/journal.pone.0219004
https://doi.org/10.1371/journal.pone.0219004
Autor:
Ilona M. Kulikovskikh, S.A. Prokhorov
Publikováno v:
Signal Processing. 120:8-12
This paper is motivated by previous research that demonstrates the importance of the explicit solution to the pole position problem. The main purpose of this paper is to solve the two-parameter pole position problem for the Meixner filters with an ex
Publikováno v:
Journal of Physics: Conference Series. 1368:052008
The paper considers the problem of accelerating the convergence of stochastic gradient descent (SGD) in an automatic way. Previous research puts forward such algorithms as Adagrad, Adadelta, RMSprop, Adam and etc. to adapt both the updates and learni