论文标题
不符合超凡的功能及其应用
Not-Quite Transcendental Functions and their Applications
论文作者
论文摘要
先验函数（例如指数和对数）出现在一系列广泛的计算域中：从曲线坐标中的仿真到插值到机器学习。不幸的是，它们通常很昂贵。在本说明中，我们认为在许多情况下，该函数的属性比确切的功能形式更重要。我们提出的不是先验的新功能，可以用作在许多设置中的指数和对数置换式替换，从而获得显着的性能提升。我们表明，对于某些应用程序，使用这些功能根本不会下降准确性，因为它们是自己的准确表示，即使不是原始的先验功能，也不会下降。
Transcendental functions, such as exponentials and logarithms, appear in a broad array of computational domains: from simulations in curvilinear coordinates, to interpolation, to machine learning. Unfortunately they are typically expensive to compute accurately. In this note, we argue that in many cases, the properties of the function matters more than the exact functional form. We present new functions, which are not transcendental, that can be used as drop-in replacements for the exponential and logarithm in many settings for a significant performance boost. We show that for certain applications using these functions result in no drop in the accuracy at all, as they are perfectly accurate representations of themselves, if not the original transcendental functions.
