Efficiently Provable Approximations for Non-Polynomial Functions

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Zero-Knowledge Proofs (ZKPs) are now widely used to verify the correctness of various types of computations. However, despite phenomenal advancements, current ZKPs are inefficient for applications that need accurate evaluation of non-polynomial functions over floating-point numbers, such as machine learning, decentralized finance, scientific computing, and geolocation. Current state-of-the-art approaches typically emulate floating-point numbers using fixed-point representations (via quantizatio