On robust randomized neural networks for regression: a comprehensive review and evaluation
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DOI: 10.1007/s00521-020-04994-5
Abstract: Data from real-world regression problems are quite often contaminated with outliers. In order to efficiently handle such undesirable samples, robust parameter estimation methods have been incorporated into randomized neural network (RNN) models, usually replacing the… read more here.
Keywords: rnn models; neural networks; robust randomized; randomized neural ... See more keywords
Recurrent Neural Networks: An Embedded Computing Perspective
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.2982416
Abstract: Recurrent Neural Networks (RNNs) are a class of machine learning algorithms used for applications with time-series and sequential data. Recently, there has been a strong interest in executing RNNs on embedded devices. However, difficulties have… read more here.
Keywords: rnn models; embedded computing; neural networks; networks embedded ... See more keywords