A Power Transform
This work proposes a foundational mathematical tool with potential broad applications across machine learning and statistics.
The authors introduced a novel power transform that serves as a unifying framework for loss functions, kernel functions, probability distributions, bump functions, and neural network activation functions, though no concrete numerical results were provided.
Power transforms, such as the Box-Cox transform and Tukey's ladder of powers, are a fundamental tool in mathematics and statistics. These transforms are primarily used for normalizing and standardizing datasets, effectively by raising values to a power. In this work I present a novel power transform, and I show that it serves as a unifying framework for wide family of loss functions, kernel functions, probability distributions, bump functions, and neural network activation functions.