Statistical learning theory provides the theoretical basis for many of
today's machine learning algorithms. In this article we attempt to give a
gentle, non-technical overview over the key ideas and insights of statistical
learning theory. We target at a broad audience, not necessarily machine
learning researchers. This paper can serve as a starting point for people who
want to get an overview on the field before diving into technical details.
Description
[0810.4752] Statistical Learning Theory: Models, Concepts, and Results
%0 Journal Article
%1 vonluxburg2008statistical
%A von Luxburg, Ulrike
%A Schoelkopf, Bernhard
%D 2008
%K learning mathematics readings stats theory
%T Statistical Learning Theory: Models, Concepts, and Results
%U http://arxiv.org/abs/0810.4752
%X Statistical learning theory provides the theoretical basis for many of
today's machine learning algorithms. In this article we attempt to give a
gentle, non-technical overview over the key ideas and insights of statistical
learning theory. We target at a broad audience, not necessarily machine
learning researchers. This paper can serve as a starting point for people who
want to get an overview on the field before diving into technical details.
@article{vonluxburg2008statistical,
abstract = {Statistical learning theory provides the theoretical basis for many of
today's machine learning algorithms. In this article we attempt to give a
gentle, non-technical overview over the key ideas and insights of statistical
learning theory. We target at a broad audience, not necessarily machine
learning researchers. This paper can serve as a starting point for people who
want to get an overview on the field before diving into technical details.},
added-at = {2020-10-17T17:13:19.000+0200},
author = {von Luxburg, Ulrike and Schoelkopf, Bernhard},
biburl = {https://www.bibsonomy.org/bibtex/281cf0e86b93210e03cd631f493f7a361/kirk86},
description = {[0810.4752] Statistical Learning Theory: Models, Concepts, and Results},
interhash = {c01e40a29d82efae067c3bf062e721f1},
intrahash = {81cf0e86b93210e03cd631f493f7a361},
keywords = {learning mathematics readings stats theory},
note = {cite arxiv:0810.4752},
timestamp = {2020-10-17T17:13:19.000+0200},
title = {Statistical Learning Theory: Models, Concepts, and Results},
url = {http://arxiv.org/abs/0810.4752},
year = 2008
}