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	<title>Memtropy &#187; Neural Networks</title>
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	<description>Signals from the Noise</description>
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		<title>Random Learning Rates in Perceptrons</title>
		<link>http://memtropy.com/random-learning-rates-in-perceptrons/</link>
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		<pubDate>Mon, 17 Nov 2008 23:55:04 +0000</pubDate>
		<dc:creator>Tomek</dc:creator>
				<category><![CDATA[Neural Networks]]></category>
		<category><![CDATA[Perceptron]]></category>

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		<description><![CDATA[Using a random learning factor instead of a fixed one to determine the change of the weight of the connections in a neural network, such as a simple perceptron, improves precision greatly.
The random() function in Python provides a pseudo-random x: 0&#60;=x&#60;1, and should average 0.5. So taking one tenth of that, the learning factor fluctuates [...]]]></description>
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