Local Learning

By Chris Atkeson
College of Computing
Georgia Institute of Technology

What is Local Learning?

Reviews, Overviews, and Surveys

An overview of work on local learning algorithms is given by:
Atkeson, C. G., Moore, A. W., & Schaal, S. (submitted). Locally Weighted Learning. Artificial Intelligence Review.

An overview of local learning applied to robots is given by:
Atkeson, C. G., Moore, A. W., & Schaal, S. (submitted). Locally Weighted Learning for Control. Artificial Intelligence Review.

Overviews of local regression are given in:
Cleveland, W. S. and C. Loader. Smoothing by Local Regression: Principles and Methods.
Fan, J. Local Modeling

A book is available:
Jianqing Fan and Irene Gijbels
Local Polynomial Modeling and its Applications
Chapman and Hall, London, 1996.

Software for local regression is available:

Recent ATT/Bell Labs work.
Older ATT/Bell Labs work. Also available from ftp://ftp.netlib.org/a/loess
Very old ATT/Bell Labs work.
Andrew Moore's work at CMU.
Stefan Schaal's work at ATR, GT, and MIT.
Local polynomial regression fitting with Epanechnikov weights or ridging, and MATLAB Smoothing Toolbox from the Department of Biostatistics at unizh.ch.
Locally parametric regression estimation: DOS program by Andrzej S. Kozek.


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If you have any comments or hotlinks to add about projects related to what we do, please let cga@cc.gatech.edu know.

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