Can machine learning identify interesting mathematics? An exploration using empirically observed laws

Wu, Chai Wah

arXiv.org Artificial Intelligence 

We explore the possibility of using machine learning to identify interesting mathematical structures by using certain quantities that serve as fingerprints. In particular, we extract features from integer sequences using two empirical laws: Benford's law and Taylor's law and experiment with various classifiers to identify whether a sequence is nice, important, multiplicative, easy to compute or related to primes or palindromes.

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