<?xml version="1.0"?>
<feed xmlns="http://www.w3.org/2005/Atom" xml:lang="en">
	<id>https://machinelearning.subwiki.org/w/index.php?action=history&amp;feed=atom&amp;title=First-order_iterative_learning_algorithm</id>
	<title>First-order iterative learning algorithm - Revision history</title>
	<link rel="self" type="application/atom+xml" href="https://machinelearning.subwiki.org/w/index.php?action=history&amp;feed=atom&amp;title=First-order_iterative_learning_algorithm"/>
	<link rel="alternate" type="text/html" href="https://machinelearning.subwiki.org/w/index.php?title=First-order_iterative_learning_algorithm&amp;action=history"/>
	<updated>2026-04-24T20:09:08Z</updated>
	<subtitle>Revision history for this page on the wiki</subtitle>
	<generator>MediaWiki 1.41.2</generator>
	<entry>
		<id>https://machinelearning.subwiki.org/w/index.php?title=First-order_iterative_learning_algorithm&amp;diff=47&amp;oldid=prev</id>
		<title>Vipul: /* Memoryless first-order iterative learning algorithm */</title>
		<link rel="alternate" type="text/html" href="https://machinelearning.subwiki.org/w/index.php?title=First-order_iterative_learning_algorithm&amp;diff=47&amp;oldid=prev"/>
		<updated>2014-06-18T23:57:42Z</updated>

		<summary type="html">&lt;p&gt;&lt;span dir=&quot;auto&quot;&gt;&lt;span class=&quot;autocomment&quot;&gt;Memoryless first-order iterative learning algorithm&lt;/span&gt;&lt;/span&gt;&lt;/p&gt;
&lt;table style=&quot;background-color: #fff; color: #202122;&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;
				&lt;col class=&quot;diff-content&quot; /&gt;
				&lt;tr class=&quot;diff-title&quot; lang=&quot;en&quot;&gt;
				&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 23:57, 18 June 2014&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-l7&quot;&gt;Line 7:&lt;/td&gt;
&lt;td colspan=&quot;2&quot; class=&quot;diff-lineno&quot;&gt;Line 7:&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class=&quot;diff-marker&quot;&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;A memoryless first-order iterative learning algorithm has the following form of rule for each iteration:&lt;/div&gt;&lt;/td&gt;&lt;td class=&quot;diff-marker&quot;&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;A memoryless first-order iterative learning algorithm has the following form of rule for each iteration:&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class=&quot;diff-marker&quot;&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;br&gt;&lt;/td&gt;&lt;td class=&quot;diff-marker&quot;&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;br&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class=&quot;diff-marker&quot; data-marker=&quot;−&quot;&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;New parameter vector = Explicit function(Old parameter vector, estimated &lt;del style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;gradient vector for &lt;/del&gt;cost function, estimated cost function)&lt;/div&gt;&lt;/td&gt;&lt;td class=&quot;diff-marker&quot; data-marker=&quot;+&quot;&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;New parameter vector = Explicit function(Old parameter vector, estimated cost function, estimated &lt;ins style=&quot;font-weight: bold; text-decoration: none;&quot;&gt;gradient vector for &lt;/ins&gt;cost function)&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class=&quot;diff-marker&quot;&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;br&gt;&lt;/td&gt;&lt;td class=&quot;diff-marker&quot;&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;br&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class=&quot;diff-marker&quot;&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;A slight variant is:&lt;/div&gt;&lt;/td&gt;&lt;td class=&quot;diff-marker&quot;&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;A slight variant is:&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;/table&gt;</summary>
		<author><name>Vipul</name></author>
	</entry>
	<entry>
		<id>https://machinelearning.subwiki.org/w/index.php?title=First-order_iterative_learning_algorithm&amp;diff=39&amp;oldid=prev</id>
		<title>Vipul: Created page with &quot;==Definition==  A &#039;&#039;&#039;first-order iterative learning algorithm&#039;&#039;&#039; is an iterative learning algorithm where each iteration of the algorithm uses only first-order information...&quot;</title>
		<link rel="alternate" type="text/html" href="https://machinelearning.subwiki.org/w/index.php?title=First-order_iterative_learning_algorithm&amp;diff=39&amp;oldid=prev"/>
		<updated>2014-06-18T23:04:00Z</updated>

		<summary type="html">&lt;p&gt;Created page with &amp;quot;==Definition==  A &amp;#039;&amp;#039;&amp;#039;first-order iterative learning algorithm&amp;#039;&amp;#039;&amp;#039; is an &lt;a href=&quot;/w/index.php?title=Iterative_learning_algorithm&amp;amp;action=edit&amp;amp;redlink=1&quot; class=&quot;new&quot; title=&quot;Iterative learning algorithm (page does not exist)&quot;&gt;iterative learning algorithm&lt;/a&gt; where each iteration of the algorithm uses only first-order information...&amp;quot;&lt;/p&gt;
&lt;p&gt;&lt;b&gt;New page&lt;/b&gt;&lt;/p&gt;&lt;div&gt;==Definition==&lt;br /&gt;
&lt;br /&gt;
A &amp;#039;&amp;#039;&amp;#039;first-order iterative learning algorithm&amp;#039;&amp;#039;&amp;#039; is an [[iterative learning algorithm]] where each iteration of the algorithm uses only first-order information about the preceding iteration.&lt;br /&gt;
&lt;br /&gt;
===Memoryless first-order iterative learning algorithm===&lt;br /&gt;
&lt;br /&gt;
A memoryless first-order iterative learning algorithm has the following form of rule for each iteration:&lt;br /&gt;
&lt;br /&gt;
New parameter vector = Explicit function(Old parameter vector, estimated gradient vector for cost function, estimated cost function)&lt;br /&gt;
&lt;br /&gt;
A slight variant is:&lt;br /&gt;
&lt;br /&gt;
New parameter vector = Explicit function(Old parameter vector, estimated gradient vector for cost function, estimated cost function, number of iterations so far)&lt;br /&gt;
&lt;br /&gt;
Such an algorithm uses the number of iterations so far in determining the new parameter vector, but does not use any other information on the past history of iterations.&lt;br /&gt;
&lt;br /&gt;
An example of this is [[gradient descent with constant learning rate]].&lt;/div&gt;</summary>
		<author><name>Vipul</name></author>
	</entry>
</feed>