Discover how regularization in machine learning can enhance model fit by preventing overfitting and promoting generalization across datasets.

The implementation for the NeurIPS2020 paper "MMA Regularization: Decorrelating Weights of Neural Networks by Maximizing the Minimal Angles", containing MMA ...

This paper introduces the potential of intelligent Bayesian regularization backpropagation neuro computing (IBRBNC) for the precise estimation of state features of underwater passive object. The ...

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Regularization lowered the likelihood of model overfitting by restricting the model’s capacity to learn; however, these restrictions resulted in the loss of some image features during learning and an ...

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Linear normalization, which is most common, involves shifting the number axis so the data is balanced around zero, and then ...

adding a sparse regularization layer between reservoirs can enhance the class definition of GVSD-ESN. Finally, the effectiveness of the proposed method is verified in an electrical drive systems.