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Journal Article

Statistische Lerntheorie und Empirische Inferenz

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Schölkopf,  B
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Jahrbuch2004-Schoelkopf.pdf
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Citation

Schölkopf, B. (2004). Statistische Lerntheorie und Empirische Inferenz. Jahrbuch der Max-Planck-Gesellschaft, 2004, 377-382.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0013-DA7F-7
Abstract
Statistical learning theory studies the process of inferring regularities from empirical data. The fundamental problem is what is called generalization: how it is possible to infer a law which will be valid for an infinite number of future observations, given only a finite amount of data? This problem hinges upon fundamental issues of statistics and science in general, such as the problems of complexity of explanations, a priori knowledge, and representation of data.