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Statistische Lerntheorie und Empirische Inferenz

2004

Miscellaneous

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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.

Author(s): Schölkopf, B.
Journal: Jahrbuch der Max-Planck-Gesellschaft
Volume: 2004
Pages: 377-382
Year: 2004
Day: 0

Department(s): Empirische Inferenz
Bibtex Type: Miscellaneous (misc)

Digital: 0
Language: de
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik

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BibTex

@misc{2811,
  title = {Statistische Lerntheorie und Empirische Inferenz},
  author = {Sch{\"o}lkopf, B.},
  journal = {Jahrbuch der Max-Planck-Gesellschaft},
  volume = {2004},
  pages = {377-382},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  year = {2004}
}