## Stochastic Learning

This paper summarizes my lecture at the Machine Learning Summer School 2003, Tübingen.

Abstract: This contribution presents an overview of the theoretical and practical aspects of the broad family of learning algorithms based on Stochastic Gradient Descent, including Perceptrons, Adalines, K-Means, LVQ, Multi-Layer Networks, and Graph Transformer Networks.

Léon Bottou: Stochastic Learning, Advanced Lectures on Machine Learning, 146-168, Edited by Olivier Bousquet and Ulrike von Luxburg, Lecture Notes in Artificial Intelligence, LNAI 3176, Springer Verlag, Berlin, 2004.
@incollection{bottou-mlss-2004,
author = {Bottou, L\'{e}on},
title = {Stochastic Learning},
booktitle = {Advanced Lectures on Machine Learning},
pages = {146-168},
publisher = {Springer Verlag},
year = {2004},
editor = {Bousquet, Olivier and von Luxburg, Ulrike},
series = {Lecture Notes in Artificial Intelligence, LNAI~3176},
}