Neirotti, Juan (2012). Learning in ultrametric committee machines. Journal of Statistical Physics, 149 (5), pp. 887-897.
Abstract
The problem of learning by examples in ultrametric committee machines (UCMs) is studied within the framework of statistical mechanics. Using the replica formalism we calculate the average generalization error in UCMs with L hidden layers and for a large enough number of units. In most of the regimes studied we find that the generalization error, as a function of the number of examples presented, develops a discontinuous drop at a critical value of the load parameter. We also find that when L>1 a number of teacher networks with the same number of hidden layers and different overlaps induce learning processes with the same critical points.
Publication DOI: | https://doi.org/10.1007/s10955-012-0636-1 |
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Divisions: | College of Engineering & Physical Sciences > Systems analytics research institute (SARI) Aston University (General) |
Additional Information: | The original publication is available at www.springerlink.com |
Uncontrolled Keywords: | multilayered networks,learning by examples,Statistical and Nonlinear Physics,Mathematical Physics |
Publication ISSN: | 1572-9613 |
Last Modified: | 28 Nov 2024 08:05 |
Date Deposited: | 20 Dec 2012 09:57 |
Full Text Link: |
http://www.spri ... 35847k88l8h18n/ |
Related URLs: |
http://www.scop ... tnerID=8YFLogxK
(Scopus URL) |
PURE Output Type: | Article |
Published Date: | 2012-11 |
Published Online Date: | 2012-11-21 |
Authors: |
Neirotti, Juan
(
0000-0002-2409-8917)
|