Zobrazeno 1 - 10
of 60
pro vyhledávání: '"Bernhard Freudenthaler"'
Publikováno v:
Algorithms, Vol 16, Iss 9, p 450 (2023)
In order to develop machine learning and deep learning models that take into account the guidelines and principles of trustworthy AI, a novel information theoretic approach is introduced in this article. A unified approach to privacy-preserving inter
Externí odkaz:
https://doaj.org/article/c84932df07ed436fa019fc8a3a6a51b5
Autor:
Jorge Martinez-Gil, Georg Buchgeher, David Gabauer, Bernhard Freudenthaler, Dominik Filipiak, Anna Fensel
Publikováno v:
Procedia Computer Science, 200, 944-953
Procedia Computer Science 200 (2022)
Procedia Computer Science 200 (2022)
In the industrial domain, developing solutions that allow the identification, understanding, and correction of faults is essential due to the cost of handling such situations. However, to date, there are not many solutions capable of facilitating the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e86a61cffce235bb1879d2e5ca08181c
https://doi.org/10.1016/j.procs.2022.01.292
https://doi.org/10.1016/j.procs.2022.01.292
Publikováno v:
IEEE Transactions on Fuzzy Systems. 29:3873-3886
This study presents an explainable fuzzy theoretic nonparametric deep model for an analysis of heart rate variability in application to stress assessment. We are concerned with the development of a model that evaluates and explains a short-time (3-5
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::76dce878ac5c83efb1986a7c519d7c3a
https://doi.org/10.1109/tfuzz.2020.3029284
https://doi.org/10.1109/tfuzz.2020.3029284
Publikováno v:
International Journal of Approximate Reasoning. 131:1-29
This paper introduces a variational analysis approach to the learning of a deep model formed via a nested composition of mappings. The fuzzy sets, being characterized by Gaussian type of membership functions, are used to represent unknown functions a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f1f87a80724ac076531f8d23cc31c832
https://doi.org/10.1016/j.ijar.2020.12.021
https://doi.org/10.1016/j.ijar.2020.12.021
Publikováno v:
Information Sciences. 546:87-120
This study introduces a privacy-preserving framework for distributed deep fuzzy learning. Assuming training data as private, the problem of learning of local deep fuzzy models is considered in a distributed setting under differential privacy framewor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::51bd365067f74c6655a84f756f7c97f1
https://doi.org/10.1016/j.ins.2020.07.044
https://doi.org/10.1016/j.ins.2020.07.044
Publikováno v:
Procedia Computer Science. 180:466-475
In various industrial production environments a burn-in phase of a specific settling-length precedes a stable (i.e. steady-state, stationary) process mode. The identification of the corresponding physical parameters may be difficult to perform in the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7fe2829e82414aaee62608bbd9889be0
https://doi.org/10.1016/j.procs.2021.01.263
https://doi.org/10.1016/j.procs.2021.01.263
Autor:
Mohit Kumar, Bernhard Freudenthaler
Publikováno v:
IEEE Transactions on Fuzzy Systems. 28:3345-3359
The application of fuzzy theory to deep learning is limited, 1) under the realm of deep neural networks, 2) to the parametric form of modeling, and 3) relying on gradient-descent-based numerical algorithms for optimization because of lack of analytic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::057f42945ab53af512649ef1c3bf0b0e
https://doi.org/10.1109/tfuzz.2019.2950636
https://doi.org/10.1109/tfuzz.2019.2950636
Publikováno v:
Procedia Manufacturing. 42:524-527
A transformation of unimodal multivariate data is introduced for increased precision in the estimation of the exponential decay type of the underlying density. The transformation renders the contour lines of the probability density function more unif
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3382a61501a12a603f6354dfdf4bd4f0
https://doi.org/10.1016/j.promfg.2020.02.038
https://doi.org/10.1016/j.promfg.2020.02.038
Publikováno v:
Communications in Computer and Information Science ISBN: 9783031143427
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ee15f778dc51f16b6169fc4afce44e7d
https://doi.org/10.1007/978-3-031-14343-4_6
https://doi.org/10.1007/978-3-031-14343-4_6
Publikováno v:
Computer Aided Systems Theory – EUROCAST 2022 ISBN: 9783031253119
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7cb4272c8a7402df8febaeb9ef43b041
https://doi.org/10.1007/978-3-031-25312-6_65
https://doi.org/10.1007/978-3-031-25312-6_65