Header logo is

Statistische Lerntheorie und Empirische Inferenz

2004

Miscellaneous

ei


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

Links: PDF
Web

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},
  doi = {}
}