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• W2051265083 abstract "Extreme learning machines are randomly initialized single-hidden layer feed-forward neural networks where the training is restricted to the output weights in order to achieve fast learning with good performance. This contribution shows how batch intrinsic plasticity, a novel and efficient scheme for input specific tuning of non-linear transfer functions, and ridge regression can be combined to optimize extreme learning machines without searching for a suitable hidden layer size. We show that our scheme achieves excellent performance on a number of standard regression tasks and regression applications from robotics." @default.
• W2051265083 created "2016-06-24" @default.
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• W2051265083 date "2013-02-01" @default.
• W2051265083 modified "2023-10-03" @default.
• W2051265083 title "Optimizing extreme learning machines via ridge regression and batch intrinsic plasticity" @default.
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• W2051265083 doi "https://doi.org/10.1016/j.neucom.2012.01.041" @default.
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