Zobrazeno 1 - 10
of 252
pro vyhledávání: '"Thierry Denœux"'
Autor:
Thierry Denoeux
Publikováno v:
Array, Vol 1, Iss , Pp - (2019)
Externí odkaz:
https://doaj.org/article/005889597200487fb8a60bf9c467dbb0
Publikováno v:
International Journal of Computational Intelligence Systems, Vol 8, Iss 1 (2015)
This paper introduces a new type of statistical model: the interval-valued linear model, which describes the linear relationship between an interval-valued output random variable and real-valued input variables. Firstly, notions of variance and covar
Externí odkaz:
https://doaj.org/article/18454e3989d8429690a960cfc697cb0e
Publikováno v:
EURASIP Journal on Advances in Signal Processing, Vol 2011 (2011)
Externí odkaz:
https://doaj.org/article/d794c63de9304c79bd194c722bb61c6d
Publikováno v:
Neurocomputing. 535:40-52
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 36:7585-7593
Multi-view deep learning is performed based on the deep fusion of data from multiple sources, i.e. data with multiple views. However, due to the property differences and inconsistency of data sources, the deep learning results based on the fusion of
Autor:
Thierry Denœux
We introduce a neural network model for regression in which prediction uncertainty is quantified by Gaussian random fuzzy numbers (GRFNs), a newly introduced family of random fuzzy subsets of the real line that generalizes both Gaussian random variab
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1688237cec48162cf1c0437d24245bf2
https://doi.org/10.36227/techrxiv.21791831.v2
https://doi.org/10.36227/techrxiv.21791831.v2
Publikováno v:
International Journal of Approximate Reasoning. 141:1-4
Publikováno v:
International Journal of Approximate Reasoning. 141:5-10
In this article, we propose a general framework for the development of external evaluation measures for soft clustering. Our proposal is based on the interpretation of soft clustering as representing uncertain information about an underlying, unknown
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f6a4c461b693a4769c887ec7cd83d82e
https://hdl.handle.net/10281/401877
https://hdl.handle.net/10281/401877
Publikováno v:
Neurocomputing
Neurocomputing, Elsevier, 2021, 450, pp.275-293. ⟨10.1016/j.neucom.2021.03.066⟩
Neurocomputing, Elsevier, 2021, 450, pp.275-293. ⟨10.1016/j.neucom.2021.03.066⟩
International audience; We propose a new classifier based on Dempster-Shafer (DS) theory and a convolutional neural network (CNN) architecture for set-valued classification. In this classifier, called the evidential deep-learning classifier, convolut