(Enter summary)
Abstract: Structural learning with forgetting is an established
method of using Laplace regularization to generate skeletal artificial
neural networks. In this paper we develop a continuous
dynamical system model of regularization in which the associated
regularization parameter is generalized to be a time-varying
function. Analytic results are obtained for a Laplace regularizer
and a quadratic error surface by solving a different linear system
in each region of the weight space. This model also enables... (Update)
Context of citations to this paper: More
.... structural learning with forgetting in which the small weights are dropped off through regularization parameters or decayed values [14]. The other way is using BackPropagation Through Time (BPTT) in which the number of parameters in the network can be confined with the memory...
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BibTeX entry: (Update)
Miller D. A., and Zurada, J. M. A dynamical system perspective of structural learning with forgetting, IEEE Transactions on Neural Networks, vol. 9, no. 3, pp. 508-515, 1998. http://citeseer.ist.psu.edu/miller98dynamical.html More
@article{ miller98dynamical,
author = "D. A. Miller and J. M. Zurada",
title = "A Dynamical System Perspective of Structural Learning with Forgetting",
journal = "IEEE Transactions on Neural Networks",
volume = "9",
number = "3",
month = "May",
pages = "508--515",
year = "1998",
url = "citeseer.ist.psu.edu/miller98dynamical.html" }
Citations (may not include all citations):
1662
Neural Networks for Pattern Recognition (context) - Bishop - 1995
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A practical Bayesian framework for backpropagation networks (context) - MacKay - 1992
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Introduction to Artificial Neural Systems (context) - Zurada - 1992
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Pruning algorithms---A survey (context) - Reed - 1993
55
Applied Linear Algebra (context) - Noble, Daniel - 1977
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Advanced Methods in Neural Computing (context) - Wasserman - 1993
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Bayesian regularization and pruning using a Laplace prior (context) - Williams - 1995
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Structural learning with forgetting (context) - Ishikawa - 1996
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Pruning via dynamic adaptation of the forgetting rate in str.. (context) - Miller, Zurada et al. - 1996
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Dynamics of structural learning with an adaptive forgetting .. (context) - Miller, Zurada - 1997
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