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Latent Connection
Learning Acquisition Time
Learning Algorithm
Learning Method
Learning Rate
Leibniz, Gottfried
Leonard Kaczmarek
Levitan, Irwin B.
Liar's Paradox
Limbic System
Local Minima
Local Minimum
Loligo Forbesi
Loligo Forbesii
Loligo Pealei
Long Term Depression
Long Term Potentiation
Lubbock, John

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(C) Copyright 2008-2021
Dominic John Repici
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Local Minimum

Specifically, with regard to neural networks, it is a state that a learning neural network sometimes gets into, where the weight adjustments for one or more training patterns simply offset the adjustments performed for a previously trained pattern. The previously trained pattern is not in its ideal desired output mapping, but is stuck in a less than ideal "local" response mapping, referred to as a local minimum. This state can sometimes be avoided by randomly jogging the connection weights (weight jogging). The underlying concept of a local minimum is often spoken of in the plural: local minima.

It is generally asserted that lower is better. That is, lower represents the more correct solution or the more desired, or ideal, state. This is leaving a lot of loose ends, of course, since adaptive systems tend to get very intertwined with philosophically unsettled issues when you begin to consider things like correctness.

Graph showing local minimums and a global minimum

Graph showing local minimums and a global minimum

Graph showing local minimums and a global minimum

Also: Weight Jogging        


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