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	<title>Publications:Training neural networks by stochastic optimisation - Revision history</title>
	<link rel="self" type="application/atom+xml" href="https://mw.hh.se/caisr/index.php?action=history&amp;feed=atom&amp;title=Publications%3ATraining_neural_networks_by_stochastic_optimisation"/>
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	<updated>2026-04-04T17:11:08Z</updated>
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	<entry>
		<id>https://mw.hh.se/caisr/index.php?title=Publications:Training_neural_networks_by_stochastic_optimisation&amp;diff=2808&amp;oldid=prev</id>
		<title>Slawek at 20:39, 30 September 2016</title>
		<link rel="alternate" type="text/html" href="https://mw.hh.se/caisr/index.php?title=Publications:Training_neural_networks_by_stochastic_optimisation&amp;diff=2808&amp;oldid=prev"/>
		<updated>2016-09-30T20:39:08Z</updated>

		<summary type="html">&lt;p&gt;&lt;/p&gt;
&lt;table class=&quot;diff diff-contentalign-left diff-editfont-monospace&quot; data-mw=&quot;interface&quot;&gt;
				&lt;col class=&quot;diff-marker&quot; /&gt;
				&lt;col class=&quot;diff-content&quot; /&gt;
				&lt;col class=&quot;diff-marker&quot; /&gt;
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				&lt;td colspan=&quot;2&quot; style=&quot;background-color: #fff; color: #202122; text-align: center;&quot;&gt;← Older revision&lt;/td&gt;
				&lt;td colspan=&quot;2&quot; style=&quot;background-color: #fff; color: #202122; text-align: center;&quot;&gt;Revision as of 20:39, 30 September 2016&lt;/td&gt;
				&lt;/tr&gt;&lt;tr&gt;&lt;td colspan=&quot;2&quot; class=&quot;diff-lineno&quot; id=&quot;mw-diff-left-l4&quot; &gt;Line 4:&lt;/td&gt;
&lt;td colspan=&quot;2&quot; class=&quot;diff-lineno&quot;&gt;Line 4:&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class=&#039;diff-marker&#039;&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;{{PublicationSetupTemplate|Author=Antanas Verikas, Adas Gelzinis&lt;/div&gt;&lt;/td&gt;&lt;td class=&#039;diff-marker&#039;&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;{{PublicationSetupTemplate|Author=Antanas Verikas, Adas Gelzinis&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class=&#039;diff-marker&#039;&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;|PID=286845&lt;/div&gt;&lt;/td&gt;&lt;td class=&#039;diff-marker&#039;&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;|PID=286845&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class=&#039;diff-marker&#039;&gt;−&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;|Name=Verikas, Antanas &lt;del class=&quot;diffchange diffchange-inline&quot;&gt;[&lt;/del&gt;av&lt;del class=&quot;diffchange diffchange-inline&quot;&gt;] [&lt;/del&gt;0000-0003-2185-8973&lt;del class=&quot;diffchange diffchange-inline&quot;&gt;] &lt;/del&gt;(Högskolan i Halmstad &lt;del class=&quot;diffchange diffchange-inline&quot;&gt;[&lt;/del&gt;2804&lt;del class=&quot;diffchange diffchange-inline&quot;&gt;]&lt;/del&gt;, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE) &lt;del class=&quot;diffchange diffchange-inline&quot;&gt;[&lt;/del&gt;3905&lt;del class=&quot;diffchange diffchange-inline&quot;&gt;]&lt;/del&gt;, Halmstad Embedded and Intelligent Systems Research (EIS) &lt;del class=&quot;diffchange diffchange-inline&quot;&gt;[&lt;/del&gt;3938&lt;del class=&quot;diffchange diffchange-inline&quot;&gt;]&lt;/del&gt;);Gelzinis, Adas (Department of Applied Electronics, Kaunas University of Technology, Lithuania)&lt;/div&gt;&lt;/td&gt;&lt;td class=&#039;diff-marker&#039;&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;|Name=Verikas, Antanas &lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;(&lt;/ins&gt;av&lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;) (&lt;/ins&gt;0000-0003-2185-8973&lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;) &lt;/ins&gt;(Högskolan i Halmstad &lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;(&lt;/ins&gt;2804&lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;)&lt;/ins&gt;, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE) &lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;(&lt;/ins&gt;3905&lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;)&lt;/ins&gt;, Halmstad Embedded and Intelligent Systems Research (EIS) &lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;(&lt;/ins&gt;3938&lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;)&lt;/ins&gt;);Gelzinis, Adas (Department of Applied Electronics, Kaunas University of Technology, Lithuania)&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class=&#039;diff-marker&#039;&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;|Title=Training neural networks by stochastic optimisation&lt;/div&gt;&lt;/td&gt;&lt;td class=&#039;diff-marker&#039;&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;|Title=Training neural networks by stochastic optimisation&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class=&#039;diff-marker&#039;&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;|PublicationType=Journal Paper&lt;/div&gt;&lt;/td&gt;&lt;td class=&#039;diff-marker&#039;&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;|PublicationType=Journal Paper&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;/table&gt;</summary>
		<author><name>Slawek</name></author>
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	<entry>
		<id>https://mw.hh.se/caisr/index.php?title=Publications:Training_neural_networks_by_stochastic_optimisation&amp;diff=2742&amp;oldid=prev</id>
		<title>Slawek at 19:47, 30 September 2016</title>
		<link rel="alternate" type="text/html" href="https://mw.hh.se/caisr/index.php?title=Publications:Training_neural_networks_by_stochastic_optimisation&amp;diff=2742&amp;oldid=prev"/>
		<updated>2016-09-30T19:47:02Z</updated>

		<summary type="html">&lt;p&gt;&lt;/p&gt;
&lt;table class=&quot;diff diff-contentalign-left diff-editfont-monospace&quot; data-mw=&quot;interface&quot;&gt;
				&lt;col class=&quot;diff-marker&quot; /&gt;
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				&lt;td colspan=&quot;2&quot; style=&quot;background-color: #fff; color: #202122; text-align: center;&quot;&gt;← Older revision&lt;/td&gt;
				&lt;td colspan=&quot;2&quot; style=&quot;background-color: #fff; color: #202122; text-align: center;&quot;&gt;Revision as of 19:47, 30 September 2016&lt;/td&gt;
				&lt;/tr&gt;&lt;tr&gt;&lt;td colspan=&quot;2&quot; class=&quot;diff-lineno&quot; id=&quot;mw-diff-left-l4&quot; &gt;Line 4:&lt;/td&gt;
&lt;td colspan=&quot;2&quot; class=&quot;diff-lineno&quot;&gt;Line 4:&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class=&#039;diff-marker&#039;&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;{{PublicationSetupTemplate|Author=Antanas Verikas, Adas Gelzinis&lt;/div&gt;&lt;/td&gt;&lt;td class=&#039;diff-marker&#039;&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;{{PublicationSetupTemplate|Author=Antanas Verikas, Adas Gelzinis&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class=&#039;diff-marker&#039;&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;|PID=286845&lt;/div&gt;&lt;/td&gt;&lt;td class=&#039;diff-marker&#039;&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;|PID=286845&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class=&#039;diff-marker&#039;&gt;−&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;|Name=Verikas, Antanas [av] (Högskolan i Halmstad [2804], Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE) [3905], Halmstad Embedded and Intelligent Systems Research (EIS) [3938]);Gelzinis, Adas (Department of Applied Electronics, Kaunas University of Technology, Lithuania)&lt;/div&gt;&lt;/td&gt;&lt;td class=&#039;diff-marker&#039;&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;|Name=Verikas, Antanas [av&lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;] [0000-0003-2185-8973&lt;/ins&gt;] (Högskolan i Halmstad [2804], Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE) [3905], Halmstad Embedded and Intelligent Systems Research (EIS) [3938]);Gelzinis, Adas (Department of Applied Electronics, Kaunas University of Technology, Lithuania)&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class=&#039;diff-marker&#039;&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;|Title=Training neural networks by stochastic optimisation&lt;/div&gt;&lt;/td&gt;&lt;td class=&#039;diff-marker&#039;&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;|Title=Training neural networks by stochastic optimisation&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class=&#039;diff-marker&#039;&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;|PublicationType=Journal Paper&lt;/div&gt;&lt;/td&gt;&lt;td class=&#039;diff-marker&#039;&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;|PublicationType=Journal Paper&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td colspan=&quot;2&quot; class=&quot;diff-lineno&quot; id=&quot;mw-diff-left-l55&quot; &gt;Line 55:&lt;/td&gt;
&lt;td colspan=&quot;2&quot; class=&quot;diff-lineno&quot;&gt;Line 55:&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class=&#039;diff-marker&#039;&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;|CreatedDate=2009-12-01&lt;/div&gt;&lt;/td&gt;&lt;td class=&#039;diff-marker&#039;&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;|CreatedDate=2009-12-01&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class=&#039;diff-marker&#039;&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;|PublicationDate=2010-01-15&lt;/div&gt;&lt;/td&gt;&lt;td class=&#039;diff-marker&#039;&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;|PublicationDate=2010-01-15&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class=&#039;diff-marker&#039;&gt;−&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;|LastUpdated=&lt;del class=&quot;diffchange diffchange-inline&quot;&gt;2013&lt;/del&gt;-&lt;del class=&quot;diffchange diffchange-inline&quot;&gt;06&lt;/del&gt;-&lt;del class=&quot;diffchange diffchange-inline&quot;&gt;11&lt;/del&gt;&lt;/div&gt;&lt;/td&gt;&lt;td class=&#039;diff-marker&#039;&gt;+&lt;/td&gt;&lt;td style=&quot;color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;|LastUpdated=&lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;2014&lt;/ins&gt;-&lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;11&lt;/ins&gt;-&lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;10&lt;/ins&gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class=&#039;diff-marker&#039;&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;|diva=http://hh.diva-portal.org/smash/record.jsf?searchId=1&amp;amp;pid=diva2:286845}}&lt;/div&gt;&lt;/td&gt;&lt;td class=&#039;diff-marker&#039;&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;|diva=http://hh.diva-portal.org/smash/record.jsf?searchId=1&amp;amp;pid=diva2:286845}}&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class=&#039;diff-marker&#039;&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&amp;lt;div style=&amp;#039;display: none&amp;#039;&amp;gt;&lt;/div&gt;&lt;/td&gt;&lt;td class=&#039;diff-marker&#039;&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&amp;lt;div style=&amp;#039;display: none&amp;#039;&amp;gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;/table&gt;</summary>
		<author><name>Slawek</name></author>
	</entry>
	<entry>
		<id>https://mw.hh.se/caisr/index.php?title=Publications:Training_neural_networks_by_stochastic_optimisation&amp;diff=1108&amp;oldid=prev</id>
		<title>SlawekBot: Created page with &quot;&lt;div style=&#039;display: none&#039;&gt; == Do not edit this section == &lt;/div&gt; {{PublicationSetupTemplate|Author=Antanas Verikas, Adas Gelzinis |PID=286845 |Name=Verikas, Antanas [av] (Hö...&quot;</title>
		<link rel="alternate" type="text/html" href="https://mw.hh.se/caisr/index.php?title=Publications:Training_neural_networks_by_stochastic_optimisation&amp;diff=1108&amp;oldid=prev"/>
		<updated>2014-03-13T11:49:35Z</updated>

		<summary type="html">&lt;p&gt;Created page with &amp;quot;&amp;lt;div style=&amp;#039;display: none&amp;#039;&amp;gt; == Do not edit this section == &amp;lt;/div&amp;gt; {{PublicationSetupTemplate|Author=Antanas Verikas, Adas Gelzinis |PID=286845 |Name=Verikas, Antanas [av] (Hö...&amp;quot;&lt;/p&gt;
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|Keywords=Neural networks;Benchmarking;Convergence of numerical methods;Learning algorithms;Problem solving;Random processes;Simulated annealing;Transfer functions;Stochastic optimisation&lt;br /&gt;
|Categories=Datavetenskap (datalogi) (10201)&lt;br /&gt;
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|Abstract=&amp;lt;p&amp;gt;We present a stochastic learning algorithm for neural networks. The algorithm does not make any assumptions about transfer functions of individual neurons and does not depend on a functional form of a performance measure. The algorithm uses a random step of varying size to adapt weights. The average size of the step decreases during learning. The large steps enable the algorithm to jump over local maxima/minima, while the small ones ensure convergence in a local area. We investigate convergence properties of the proposed algorithm as well as test the algorithm on four supervised and unsupervised learning problems. We have found a superiority of this algorithm compared to several known algorithms when testing them on generated as well as real data.&amp;lt;/p&amp;gt;&lt;br /&gt;
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|CreatedDate=2009-12-01&lt;br /&gt;
|PublicationDate=2010-01-15&lt;br /&gt;
|LastUpdated=2013-06-11&lt;br /&gt;
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