Sterkenburg, Tom F. (2024) Statistical Learning Theory and Occam's Razor: The Core Argument. Minds and Machines.
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Abstract
Statistical learning theory is often associated with the principle of Occam's razor, which recommends a simplicity preference in inductive inference. This paper distills the core argument for simplicity obtainable from statistical learning theory, built on the theory's central learning guarantee for the method of empirical risk minimization. This core means-ends argument is that a simpler hypothesis class or inductive model is better because it has better learning guarantees; however, these guarantees are model-relative and so the theoretical push towards simplicity is checked by our prior knowledge.
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| Item Type: | Published Article or Volume | ||||||
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| Keywords: | machine learning, Occam's razor, induction, statistical learning theory | ||||||
| Subjects: | General Issues > Confirmation/Induction General Issues > Formal Learning Theory Specific Sciences > Artificial Intelligence > Machine Learning Specific Sciences > Probability/Statistics |
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| Depositing User: | Mr Tom Sterkenburg | ||||||
| Date Deposited: | 30 Nov 2024 13:02 | ||||||
| Last Modified: | 30 Nov 2024 13:02 | ||||||
| Item ID: | 24311 | ||||||
| Journal or Publication Title: | Minds and Machines | ||||||
| Official URL: | https://link.springer.com/article/10.1007/s11023-0... | ||||||
| DOI or Unique Handle: | 10.1007/s11023-024-09703-y | ||||||
| Subjects: | General Issues > Confirmation/Induction General Issues > Formal Learning Theory Specific Sciences > Artificial Intelligence > Machine Learning Specific Sciences > Probability/Statistics |
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| Date: | 2024 | ||||||
| URI: | https://philsci-archive.pitt.edu/id/eprint/24311 |
Available Versions of this Item
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Statistical Learning Theory and Occam's Razor: The Argument from Empirical Risk Minimization. (deposited 30 Jun 2023 12:55)
- Statistical Learning Theory and Occam's Razor: The Core Argument. (deposited 30 Nov 2024 13:02) [Currently Displayed]
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