Abstract: Neural networks (NNs) are commonly used to approximate functions based on data samples, as they are a universal function approximator for a large class of ...

Combined functions involve the operations of addition, subtraction, multiplication and division applied to two or more functions. A hybrid function is also an example of combined functions. Combined ...

Functions are fundamental in mathematics, describing relationships between inputs and outputs. For instance, linear functions are used to describe proportional relationships such as calculating cost ...

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Abstract: The choice of activation functions is crucial to deep neural networks. ReLU is a popular hand-designed activation function. Swish, the automatically searched activation function, outperforms ...

A python implementation of the algorithm used to generate optimal piecewise linear approximations of convex functions proposed by Imamoto and Tang [1]. The algorithm uses an iterative search to find ...