PhilSci Archive

Statistical Learning Theory and Occam's Razor: The Argument from Empirical Risk Minimization

Sterkenburg, Tom F. (2023) Statistical Learning Theory and Occam's Razor: The Argument from Empirical Risk Minimization. [Preprint]

[img]
Preview
Text
sltoccaerm.pdf - Draft Version

Download (428kB) | Preview

Export/Citation: EndNote | BibTeX | Dublin Core | ASCII/Text Citation (Chicago) | HTML Citation | OpenURL
Social Networking:
Share |

Item Type: Preprint
Creators:
CreatorsEmailORCID
Sterkenburg, Tom F.tom.sterkenburg@lmu.de0000-0002-4860-727X
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
Depositing User: Mr Tom Sterkenburg
Date Deposited: 30 Jun 2023 12:55
Last Modified: 30 Jun 2023 12:55
Item ID: 22259
Subjects: General Issues > Confirmation/Induction
General Issues > Formal Learning Theory
Specific Sciences > Artificial Intelligence > Machine Learning
Specific Sciences > Probability/Statistics
Date: 2023
URI: https://philsci-archive.pitt.edu/id/eprint/22259

Monthly Views for the past 3 years

Monthly Downloads for the past 3 years

Plum Analytics

Actions (login required)

View Item View Item