Minds and Machines 32 (1):13-42 (2022)

Authors
Gustavo Cevolani
IMT School For Advanced Studies Lucca
Abstract
The idea that “simplicity is a sign of truth”, and the related “Occam’s razor” principle, stating that, all other things being equal, simpler models should be preferred to more complex ones, have been long discussed in philosophy and science. We explore these ideas in the context of supervised machine learning, namely the branch of artificial intelligence that studies algorithms which balance simplicity and accuracy in order to effectively learn about the features of the underlying domain. Focusing on statistical learning theory, we show that situations exist for which a preference for simpler models provably slows down, instead of favoring, the supervised learning process. Our results shed new light on the relations between simplicity and truth approximation, which are briefly discussed in the context of both machine learning and the philosophy of science.
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DOI 10.1007/s11023-022-09592-z
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References found in this work BETA

Ockham’s Razors: A User’s Manual.Elliott Sober - 2015 - Cambridge University Press.
Making AI Meaningful Again.Jobst Landgrebe & Barry Smith - 2021 - Synthese 198 (March):2061-2081.
Simplicity.Alan Baker - 2008 - Stanford Encyclopedia of Philosophy.

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