Research report 2003 - Max Planck Institute for Biological Cybernetics

Statistical Learning Theorie and Empirical Inference

Authors
Schölkopf, Bernhard
Departments

Empirische Inferenz (Prof. Dr. Bernhard Schölkopf), MPI für biologische Kybernetik, Tübingen

Summary
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.

For the full text, see the German version.

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