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	<title>De Rerum Natura &#187; Fourier Analysis</title>
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	<link>http://www.corrada.com/blog</link>
	<description>Randomness, entropy, pattern matching, maps, geometry, knots, and scientific readings</description>
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		<title>ICML accepts precision error via L1 minimization paper</title>
		<link>http://www.corrada.com/blog/2008/04/09/icml-accepts-precision-error-via-l1-minimization-paper/</link>
		<comments>http://www.corrada.com/blog/2008/04/09/icml-accepts-precision-error-via-l1-minimization-paper/#comments</comments>
		<pubDate>Wed, 09 Apr 2008 10:48:02 +0000</pubDate>
		<dc:creator>Andrés</dc:creator>
				<category><![CDATA[Compressed Sensing]]></category>
		<category><![CDATA[Fourier Analysis]]></category>
		<category><![CDATA[Group Theory]]></category>
		<category><![CDATA[Mathematics]]></category>
		<category><![CDATA[MathML]]></category>
		<category><![CDATA[Randomness]]></category>
		<category><![CDATA[Scientific Readings]]></category>

		<guid isPermaLink="false">http://www.corrada.com/blog/?p=69</guid>
		<description><![CDATA[Our technical report on how to recover precision error estimates with $\ell_1$-minimization has been accepted by the 2008 International Conference on Machine Learning. The paper originally got three anonymous reviews. Two were positive, one strongly negative. In our response to the reviews, we agreed with the general criticism by the reviewers that one experimental demonstration [...]]]></description>
		<wfw:commentRss>http://www.corrada.com/blog/2008/04/09/icml-accepts-precision-error-via-l1-minimization-paper/feed/</wfw:commentRss>
		<slash:comments>2</slash:comments>
		</item>
		<item>
		<title>Variations in student responses to a multiple exam for latent group discovery</title>
		<link>http://www.corrada.com/blog/2008/03/13/variations-in-student-responses-to-a-multiple-exam-for-latent-group-discovery/</link>
		<comments>http://www.corrada.com/blog/2008/03/13/variations-in-student-responses-to-a-multiple-exam-for-latent-group-discovery/#comments</comments>
		<pubDate>Fri, 14 Mar 2008 00:03:37 +0000</pubDate>
		<dc:creator>Andrés</dc:creator>
				<category><![CDATA[Error Theory]]></category>
		<category><![CDATA[Fourier Analysis]]></category>
		<category><![CDATA[Group Theory]]></category>
		<category><![CDATA[Machine Learning]]></category>
		<category><![CDATA[latent labels]]></category>

		<guid isPermaLink="false">http://www.corrada.com/blog/2008/03/13/variations-in-student-responses-to-a-multiple-exam-for-latent-group-discovery/</guid>
		<description><![CDATA[Questions in an exam are detectors of student competency. Students are detectors of the correct answers in a test. What is the variation in the student&#8217;s model of the correct exam? The precision error equations can be used to construct a covariance matrix for the students instead of the questions. What makes the difference is [...]]]></description>
		<wfw:commentRss>http://www.corrada.com/blog/2008/03/13/variations-in-student-responses-to-a-multiple-exam-for-latent-group-discovery/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
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		<item>
		<title>To err is human, to study your errors is glorious</title>
		<link>http://www.corrada.com/blog/2008/02/17/to-err-is-human-to-study-your-errors-is-glorious/</link>
		<comments>http://www.corrada.com/blog/2008/02/17/to-err-is-human-to-study-your-errors-is-glorious/#comments</comments>
		<pubDate>Mon, 18 Feb 2008 01:59:33 +0000</pubDate>
		<dc:creator>Andrés</dc:creator>
				<category><![CDATA[Error Theory]]></category>
		<category><![CDATA[Fourier Analysis]]></category>
		<category><![CDATA[Group Theory]]></category>
		<category><![CDATA[Machine Learning]]></category>
		<category><![CDATA[Maps]]></category>
		<category><![CDATA[Randomness]]></category>
		<category><![CDATA[error estimation]]></category>
		<category><![CDATA[model precision]]></category>

		<guid isPermaLink="false">http://www.corrada.com/blog/2008/02/17/to-err-is-human-to-study-your-errors-is-glorious/</guid>
		<description><![CDATA[I&#8217;ve been sick all week but today has been the worst. In between my sleeping hallucinations I have been thinking a lot about a proposal I&#8217;m currently writing on the use of non-commutative harmonic analysis to study mapping error patterns. It has become clear that the approach we are advocating at the AIRS lab is [...]]]></description>
		<wfw:commentRss>http://www.corrada.com/blog/2008/02/17/to-err-is-human-to-study-your-errors-is-glorious/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
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		<title>X-raying the geometric precision error of DEMs with Fourier analysis</title>
		<link>http://www.corrada.com/blog/2008/02/02/x-raying-the-geometric-precision-error-of-dems-with-fourier-analysis/</link>
		<comments>http://www.corrada.com/blog/2008/02/02/x-raying-the-geometric-precision-error-of-dems-with-fourier-analysis/#comments</comments>
		<pubDate>Sat, 02 Feb 2008 18:10:32 +0000</pubDate>
		<dc:creator>Andrés</dc:creator>
				<category><![CDATA[Compressed Sensing]]></category>
		<category><![CDATA[Error Theory]]></category>
		<category><![CDATA[Fourier Analysis]]></category>
		<category><![CDATA[Group Theory]]></category>
		<category><![CDATA[Machine Learning]]></category>
		<category><![CDATA[Randomness]]></category>
		<category><![CDATA[DEMs]]></category>
		<category><![CDATA[symmetry group]]></category>
		<category><![CDATA[theory of geometric errors]]></category>

		<guid isPermaLink="false">http://www.corrada.com/blog/2008/02/02/x-raying-the-geometric-precision-error-of-dems-with-fourier-analysis/</guid>
		<description><![CDATA[In a previous post I mentioned a way of Fourier analyzing the geometric precision error of DEMs. Today I realized that the scheme I proposed can only account for part of the error signal. The approach I proposed is correct but it can only capture one particular aspect of the total error. The simplest way [...]]]></description>
		<wfw:commentRss>http://www.corrada.com/blog/2008/02/02/x-raying-the-geometric-precision-error-of-dems-with-fourier-analysis/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
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		<title>Fourier theory of DEM precision errors</title>
		<link>http://www.corrada.com/blog/2008/01/29/fourier-theory-of-dem-precision-errors/</link>
		<comments>http://www.corrada.com/blog/2008/01/29/fourier-theory-of-dem-precision-errors/#comments</comments>
		<pubDate>Tue, 29 Jan 2008 18:09:58 +0000</pubDate>
		<dc:creator>Andrés</dc:creator>
				<category><![CDATA[Error Theory]]></category>
		<category><![CDATA[Fourier Analysis]]></category>
		<category><![CDATA[Group Theory]]></category>
		<category><![CDATA[Maps]]></category>
		<category><![CDATA[Mathematics]]></category>
		<category><![CDATA[DEMs]]></category>
		<category><![CDATA[symmetry group]]></category>

		<guid isPermaLink="false">http://www.corrada.com/blog/?p=29</guid>
		<description><![CDATA[I&#8217;ve finished the experiments with different reconstruction matrices for the DEM precision error and I get a rock solid result independent of which reconstruction matrix I use. So my hypothesis that randomness may be used to increase the precision error was wrong. In the process, however, I have finally understood how to use the symmetry [...]]]></description>
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		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>NIPS interesting paper on group theory and Fourier analysis applied to inference</title>
		<link>http://www.corrada.com/blog/2007/12/06/nips-interesting-paper-on-group-theory-and-fourier-analysis-applied-to-inference/</link>
		<comments>http://www.corrada.com/blog/2007/12/06/nips-interesting-paper-on-group-theory-and-fourier-analysis-applied-to-inference/#comments</comments>
		<pubDate>Fri, 07 Dec 2007 01:38:42 +0000</pubDate>
		<dc:creator>Andrés</dc:creator>
				<category><![CDATA[Fourier Analysis]]></category>
		<category><![CDATA[Group Theory]]></category>
		<category><![CDATA[Machine Learning]]></category>

		<guid isPermaLink="false">http://www.corrada.com/blog/?p=25</guid>
		<description><![CDATA[This week I am at the annual Neural Information Processing Systems Conference a fascinating conference that combines many of my scientific interests on machine learning, computer vision, statistics, and natural language processing. Last night I visited the poster by Jonathan Huang on efficient inference for distributions on permutations. The paper considers the problem of how [...]]]></description>
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		<slash:comments>0</slash:comments>
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