Article View: es.comp.neuronal
Article #1321preprint on on-line unsupervised learning
From: Michael Biehl
Date: Fri, 04 Apr 1997 00:00
Date: Fri, 04 Apr 1997 00:00
63 lines
3067 bytes
3067 bytes
The following manuscript is now available via anonymous ftp
(see below for the retrieval procedure), or, alternatively from
http://www.physik.uni-wuerzburg.de/~biehl
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"Specialization processes in on-line unsupervised learning"
Michael Biehl, Ansgar Freking, Georg Reents, and Enno Schl"osser
Contribution to the
Minerva Workshop on Mesoscopics, Fractals and Neural Networks
Eilat, Israel, March 1997
Ref: WUE-ITP-97-003
Abstract
From the recent analysis of supervised learning by on-line gradient
descent in multilayered neural networks it is known that the necessary
process of student specialization can be delayed significantly. We
demonstrate that this phenomenon also occurs in various models of
unsupervised learning. A solvable model of competitive learning is
presented, which identifies prototype vectors suitable for the repre-
sentation of high--dimensional data. The specific case of two overlapping
clusters of data and a matching number of prototype vectors exhibits non-
trivial behavior like almost stationary plateau configurations. As a
second example scenario we investigate the application of Sanger's
algorithm for principal component analysis in the presence of two relevant
directions in input space. Here, the fast learning of the first principal
component may lead to an almost complete loss of initial knowledge about
the second one.
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Retrieval procedure:
unix> ftp ftp.physik.uni-wuerzburg.de
Name: anonymous Password: {your e-mail address}
ftp> cd pub/preprint/1997
ftp> binary
ftp> get WUE-ITP-97-003.ps.gz (*)
ftp> quit
unix> gunzip WUE-ITP-97-003.ps.gz
e.g. unix> lp WUE-ITP-97-003.ps [10 pages]
(*) can be replaced by "get WUE-ITP-97-003.ps". The file will then
be uncompressed before transmission (slow!).
_____________________________________________________________________
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Michael Biehl
Institut fuer Theoretische Physik
Julius-Maximilians-Universitaet Wuerzburg
Am Hubland
D-97074 Wuerzburg
email: biehl@physik.uni-wuerzburg.de
homepage: http://www.physik.uni-wuerzburg.de/~biehl
Tel.: (+49) (0)931 888 5865
" " " 5131
Fax : (+49) (0)931 888 5141
Technical Details
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X-Google-Language: ENGLISH,ASCII-7-bit X-Google-Thread: 108436,21c7377ad264fa68,start X-Google-Attributes: gid108436,public From: Michael Biehl <biehl@physik.uni-wuerzburg.de> Subject: preprint on on-line unsupervised learning Date: 1997/04/04 Message-ID: <199704040831.KAA29194@wptx08.physik.uni-wuerzburg.de> X-Deja-AN: 230736546 To: Connectionists <Connectionists@cs.cmu.edu> FTP-host: ftp.physik.uni-wuerzburg.de FTP-filename: /pub/preprint/1997/WUE-ITP-97-003.ps.gz Reply-To: neuras-list@etsiig.uniovi.es Newsgroups: es.comp.neuronal