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.

@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 = {}
}