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An upper bound on the variance of scalar multilayer perceptrons for log-concave distributions.
- Source :
-
Neurocomputing . Jun2022, Vol. 488, p540-546. 7p. - Publication Year :
- 2022
-
Abstract
- In this paper, we give an upper bound on the variance of scalar multilayer perceptrons. The distribution of the input is assumed to be the class of log-concave distributions, which includes the well-known Gaussian distribution. The activation functions of the scalar multilayer perceptrons are assumed to be differentiable and Lipschitz continuous. [ABSTRACT FROM AUTHOR]
- Subjects :
- *MULTILAYER perceptrons
*GAUSSIAN distribution
Subjects
Details
- Language :
- English
- ISSN :
- 09252312
- Volume :
- 488
- Database :
- Academic Search Index
- Journal :
- Neurocomputing
- Publication Type :
- Academic Journal
- Accession number :
- 156253066
- Full Text :
- https://doi.org/10.1016/j.neucom.2021.11.062